Nurul Zawani AliasRizana Yusof   Editors

Charting the Sustainable Future of ASEAN in Science and TechnologyProceedings from the 3rd International Conference on the Future of ASEAN (ICoFA) 2019 - Volume 2

Charting the Sustainable Future of ASEANin Science and Technology

Nurul Zawani Alias • Rizana YusofEditors

Charting the SustainableFuture of ASEAN in Scienceand TechnologyProceedings from the 3rd InternationalConference on the Future of ASEAN (ICoFA)2019 - Volume 2

123

EditorsNurul Zawani AliasUniversiti Teknologi MARA PerlisPerlis, Malaysia

Rizana YusofUniversiti Teknologi MARA PerlisPerlis, Malaysia

ISBN 978-981-15-3433-1 ISBN 978-981-15-3434-8 (eBook)https://doi.org/10.1007/978-981-15-3434-8

© Springer Nature Singapore Pte Ltd. 2020This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or partof the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations,recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmissionor information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilarmethodology now known or hereafter developed.The use of general descriptive names, registered names, trademarks, service marks, etc. in thispublication does not imply, even in the absence of a specific statement, that such names are exempt fromthe relevant protective laws and regulations and therefore free for general use.The publisher, the authors and the editors are safe to assume that the advice and information in thisbook are believed to be true and accurate at the date of publication. Neither the publisher nor theauthors or the editors give a warranty, expressed or implied, with respect to the material containedherein or for any errors or omissions that may have been made. The publisher remains neutral with regardto jurisdictional claims in published maps and institutional affiliations.

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Contents

1 Hearing Assistive Technology: Sign Language TranslationApplication for Hearing-Impaired Communication . . . . . . . . . . . . . 1Mohd Nizam Osman, Khairul Anwar Sedek, Nur Zaid Md Zain,Muhamad Amin Naim Ab Karim and Mushahadah Maghribi

2 Fish Freshness Detector Using Sensory Quality Index Methodand Digital Image Processing Evaluation . . . . . . . . . . . . . . . . . . . . 13Khairul Naim Abd.Aziz, Shameen Izwan Anthonysamy,Zamzila Erdawati Zainol, Muhammad Akmal Roslaniand Sharir Aizat Kamaruddin

3 The Impacts of Different Types of Slopes on Soil FertilityMovement of Harumanis Mango . . . . . . . . . . . . . . . . . . . . . . . . . . . 23Sharifah Norashikin Bohari, Che Ahmad Redzuan Che Romeli,Norhanani Ahmad, Amirul Ikram Azmi, Nurul Ain Mohd Zakiand Abdul Rauf Abdul Rasam

4 Quran Indexing Using Cloud Database . . . . . . . . . . . . . . . . . . . . . . 37Khairul Anwar Sedek, Noriati Roseni binti Ghazaliand Mohd Nizam Osman

5 Geospatial Site Suitability for Sustainable Property Investment . . . . 49Ernieza Suhana Mokhtar, Wan Nur Azliena Wan Mohd Zaki,Noraini Nasirun, Fatin Amirah Hanif and Idham Nugraha

6 Analysis of Organophosphorus Pesticides (OPPs) in Paddy FieldWater Using IL-DLLME . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65Sharizal Bin Hasan, Non Daina Masdar, Mohd Lias Kamal,Norizan Binti Ramli and Nurul Zawani Alias

7 The Potential of Bamboo Vinegar (Gigantochloa albociliata)as Insecticide . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79Nurul Zawani Alias, Shafinas Abdullah, Siti Shahirah Shaari,Jesmond Joel Junik, Mohd Lias Kamal and Non Daina Masdar

v

8 Tensile Strength of Polyester Composite Filledwith Bamboo Fiber . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87Noor Syafeekha Mohamad Sakdun, Nur Azrin Azlan,Nik Farhanim Imran and Hafizah Muhamad Azlan

9 NetGuard: Securing Network Environment Using IntegratedOpenVPN, Pi-Hole, and IDS on Raspberry Pi . . . . . . . . . . . . . . . . 97Abidah Mat Taib, Muhammad Tholhah Zabri, Nor Azira Mohd Radziand Evizal Abdul Kadir

10 Bilingual e-Story Book for Hearing-Impaired Students (BeSH)Toward Sustainability Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . 111Sharifah Nurulhikmah Syed Yasin, Hayati Adilin Mohd Abd Majid,Ummu Fatihah Mohd Bahrin, Siti Salbiah Hamzahand Zeti Darleena Eri

11 The Potential of Antioxidants and Phytochemicals Componentsin Fruit Waste (Peel) of Citrus hystrix and Ananas comosus . . . . . . 123Rohayu Ramli, Nureen Shahirah Ahmad Zaghluland Nor Atikah Husna Ahmad Nasir

12 The Effect of Different Animal Dung in VermicompostProduction Using Eudrilus eugeniae Worm and SpentMushroom Substrate as Vermicomposting Medium . . . . . . . . . . . . 137Norhanani Ahmad, Nurhidayah Mat Sukriand Noor Zuhairah Samsuddin

13 Biofilm Developed from Acrylated Epoxidized Soybean Oil:Preparation and Characterization . . . . . . . . . . . . . . . . . . . . . . . . . . 147Sharifah Nafisah Syed Ismail, Farah Izati Ibrahim, Khuzaimah Nazir,Noor Aishatun Majid, Nor Mazlina Abdul Wahab,Marina Mohd Shahabudin and Mithalina Zulaikha Ismail

14 Anti-microbial Properties and Toxicity Test of Stingless BeeHoney (Trigona itama), Ajwa Date (Phoenix dactylifera L.)Seeds and Their Combinations . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155Nurul Syazwina Roslan, Nur Syafiqah Rahim, Zainab Razaliand Mohd Azhar Zulkifli

15 PM2.5 Pollutant Distributions in Years 2016 and 2019Using GIS Spatial Analyst . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167Noorfatekah Talib, Nur Syahirah Mohamad Sallehuddin,Nur Amira Mohd Sa’aid and Nurhafiza Md. Saad

16 Sustainable Embedded Technology for Mouse Trap . . . . . . . . . . . . 181Norfiza Ibrahim, Azmi Abu Seman, Nadia Abdul Wahab,Aznoora Osman and Muhammad Hazim Firdaus Ismail

vi Contents

17 Determination of Antioxidant from Ubi Gadong Tubersfor Facial Soap Bar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193Non Daina Masdar, Robiatul Adawiyah Binti Roslan,Sharizal Bin Hasan and Mohd Lias Kamal

18 Coconut Oil Plasticizer as a Replacement of Petroleum Oilin Natural Rubber Compound: Physical and MechanicalProperties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203Farhana Othman and Nismahasyirah Alang Ismail

19 Histopathology Alteration of Red Hybrid Tilapia (Oreochromis Spp.)Caused by Streptococcus Agalactiae Infection . . . . . . . . . . . . . . . . . . . 215Ain Auzureen Mat Zin, Ruhil Hayati Hamdan,Mohd Hafiz Jamaludin, Jasni Sabri and Li Peng Tan

20 Ethnobotanical Study on Flowering Plants Alongwith Phytochemicals and Antioxidants Analysis on SelectedPlumeria Species . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227Nur Illani Abdul Razak, Siti Sumaiyah Syahida Hassanand Nor Atikah Husna Ahmad Nasir

21 i-Kids Science Courseware Toward Sustainability Educationfor Hearing-Impaired Students . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237Darleena Eri Zeti, Adilin Mohd Abd Majid Hayati,Nurulhikmah Syed Yasin Sharifah, Salbiah Hamzah Sitiand Raju Rajeswari

22 Phytochemical Screening and Potential DPPH RadicalScavenging Activity of Banana Peel Extract . . . . . . . . . . . . . . . . . . 249Nor Atikah Husna Ahmad Nasir, Nurul Atikah Liana Roslly,Nurul Miza Rosli and Zainab Razali

23 Newly Revised Optimal and Synchronized Timetables forGreater Kuala Lumpur Using Mixed Integer Programming . . . . . . 259Noraini Noordin and Saiyidatul Adidah Idris

24 Kinetic Modeling and Half-Life Study on Bioaugmentation of OilSludge Contaminated Soil by Single and Consortia LIBeMat Different Concentration Levels . . . . . . . . . . . . . . . . . . . . . . . . . . 271Nur Zaida Zahari and Piakong Mohd Tuah

25 A Comparative Study of the Accuracy of Regularizedand Tension Spline Interpolation Methods to Map the SurfaceWater Temperature of Pulau Tuba, Langkawi, Kedah . . . . . . . . . . 285Sharir Aizat Kamaruddin, Shaidatul Najwa Zainolabdin,Khairul Naim Abd.Aziz, Muhammad Akmal Roslani,Nur Syazwana Akmal Mohd Zohirand Nurdamia Yasmin Mustaffa Al-Bakri

Contents vii

26 Antibacterial and Insect-Repellent Activities of Cananga odorataEssential Oil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 297Syarifah Nursyimi Azlina Syed Ismail,Sharifah Sakinah Syed Soffian, Rosmawati Abdul Azizand Nordiana Suhada Mohmad Tahiruddin

27 Dosimetric Characterization of Corn Starch/Polyvinyl Alcohol(PVA) Blend as Potential Radiotherapy Bolus Material . . . . . . . . . 307Fairuzdzah Ahmad Lothfy, Salsabila Kamaruddin,Nik Kamarullah Ya Ali and Norfataha Mohd Daud

28 Dominant Tree Species Estimation for Tropical ForestUsing Pixel-Based Classification Support Vector Machine(SVM) and Object-Based Classification (OBIA) . . . . . . . . . . . . . . . 319Nurul Ain Mohd Zaki, Intan Nur Suhaida Mohd Radzi,Zulkiflee Abd Latif, Mohd Nazip Suratman, Mohd Zainee Zainaland Sharifah Norashikin Bohari

29 The Potential Area Estimation for Solar Installation Basedon Insolation Pattern Derived from LiDAR Points Cloud Data . . . . 335Nurhafiza Md Saad, Muhammad Khairil Asyraf Mohd Shukair,Noraain Mohamed Saraf, Juazer Rizal Abdul Hamid,Noorfatekah Talib and Abdul Rauf Abdul Rasam

30 Detecting Speed Violation Using Wireless Sensor Networkto Reduce Road Accidents Among Commercial Bus . . . . . . . . . . . . 351Rashidah Ramle, Haidib Mohd Haider, Muhammad Fakhrul Yusuf,Norzatul Bazamah Azman Shah, Nur Khairani Kamarudinand Rafiza Ruslan

31 Data Verification of LiDAR-Derived DEM from DifferentInterpolation Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 361Noraain Mohamed Saraf, Khairun Najwa Kamarolzaman,Nurhafiza Md Saad, Nafisah Khalid, Abdul Rauf Abdul Rasamand Ainon Nisa Othman

32 An Application of Presumptive Diagnosis for Urinary TractInfection via kNN Algorithm Approach . . . . . . . . . . . . . . . . . . . . . 377Muhammad Nabil Fikri Jamaluddin, Siti Norfahana Abdul Malik,Shukor Sanim Mohd Fauzi, Tajul Rosli Razak,Iman Hazwam Abd Halim, Abdul Hapes Mohammedand Ray Adderley JM Gining

viii Contents

33 The Investigation on the Implementation of IndustrialisedBuilding System (IBS) in Infrastructure Project: A Case Studyin Selangor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 389Juzailah Nur Yunus, Nur Atiqah Halim,Raja Nor Husna Raja Mohd Noor, Nurol Huda Dahalanand Nor Janna Tammy

34 Fuzzy Logic Water Quality Index (FWQI) Model in Determiningthe Water Quality Status of River in Penang Island . . . . . . . . . . . . 399Siti Nor Nadrah Muhamad, Mohd Fazril Izhar Mohd Idris,Nurul Izzati Husna Wahab and Wan Nurshazelin Wan Shahidan

35 Concrete Performance Using Treated POFA as a PartialReplacement of Cement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 411Nik Farhanim Imran, Mohd Afiq Mohd Azham,Md Rasul Mohamad Nor, Noor Syafeekha Mohamad Sakdun,Nor Hafida Hashim, Siti Rahimah Rosseli, Hafizah Muhamad Azlanand Muhd Norhasri Muhd Sidek

36 Characterization of Pectin Extracted from Guava PeelsUsing Deep Eutectic Solvent and Citric Acid . . . . . . . . . . . . . . . . . 421Rizana Yusof, Siti Zawani Ahmad Zaini and Mohd Azhar Azman

37 Mechanical Properties of Silane-Treated Eggshell Powderon Unsaturated Polyester Composite . . . . . . . . . . . . . . . . . . . . . . . . 435Nor Mazlina Abdul Wahab, Mohammad Azri Md Hanafiah,Dalina Samsudin, Mohd Syamaizar Mustafa, Zuliahani Ahmadand Sharifah Nafisah Syed Ismail

38 Pineapple Leaf Fibre Filled Natural Rubber Composite:The Effect of Filler Loading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 447Mohd Syamaizar Mustafa, Sharifah Nafisah Syed Ismail,Shafeera Mohd Shaipul Amini, Nor Mazlina Abdul Wahab,Noor Aishatun Majid and Muhamad Naiman Sarip

39 Green Synthesis of Silver Nanoparticles from Ananas comosusCore Extract and Their Antibacterial Activity . . . . . . . . . . . . . . . . 455Zainab Razali, Nur Wajihah Masdar,Nor Atikah Husna Ahmad Nasir, Nur Syafiqah Rahimand Roejhan Md Kawi

40 Effects of Different Ratios of 45% N, N-Dimethylformamide(DMF) Solvent in Reaction with Derived 2D Hybrid PerovskiteC6H8N2PbI3 Prepared via Nitrogen-Less Method . . . . . . . . . . . . . . 465Azliana Ramli, Mohd Nazari Abu Bakar, Suhaila Sepeai,Ab Malik Marwan Ali, Nafisah Osmanand Wan Izhan Nawawi Wan Ismail

Contents ix

41 Detection of Integron and Antibiotic Resistance Genesof Aeromonas spp. Isolated from Freshwater Fish in Pahang,Malaysia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 473Fazlina Fauzi, Ruhil Hayati Hamdan, Maizan Mohamedand Li Peng Tan

42 Characterization of Untreated and Acid Treated Natural Fillerfrom L. Oryza Sativa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 487Iqmal Che Hanah, Mohd Lias Kamal, Noor Aishatun Majid,Wahida Abdul Rahman, Sharifah Nafisah Syed Ismail,Nor Mazlina Abdul Wahab, Nur Fairuz Wahida Ibrahim,Noor Faezah Mohd Sani and Siti Nur Liyana Mamauod

43 Disease Mapping and Health Analysis Using Free and OpenSource Software for Geospatial (FOSS4G): An ExploratoryQualitative Study of Tuberculosis . . . . . . . . . . . . . . . . . . . . . . . . . . 495Muhammad Dinie Haqim Azewan and Abdul Rauf Abdul Rasam

44 E-Mosque Tourism: Discovering Mosques via GeodigitalMapping in Kuala Lumpur, Malaysia . . . . . . . . . . . . . . . . . . . . . . . 507Nurin Syarafina Mohd Hasmizi, Abdul Rauf Abdul Rasamand Noraain Mohamed Saraf

45 Sustainable Palm Oil Production Through Optimizingof Planted Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 519Wan Nurshazelin Wan Shahidan and Nor Atikah Nadzri

46 Agent-Based Encryption for Password ManagementApplication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 529Nurul Hidayah Ahmad Zukri, Nor Aimuni Md Rashid,Norkhushaini Awang and Zuhri Arafah Zulkifli

47 A Single Objective Fuzzy Linear Programming for OptimizingHand Socks Production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 543Wan Nurshazelin Wan Shahidan, Nurul ′Ain Rusydiah Mohd Rodziand Siti Nor Nadrah Muhamad

48 GeoPark Management and GIS: Geospatial Tree InformationInventory System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 553Hanisah Othman, Abdul Rauf Abdul Rasam and Norajlin Jaini

Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 569

x Contents

Chapter 1Hearing Assistive Technology: SignLanguage Translation Applicationfor Hearing-Impaired Communication

Mohd Nizam Osman , Khairul Anwar Sedek, Nur Zaid Md Zain,Muhamad Amin Naim Ab Karim and Mushahadah Maghribi

Abstract Sign Language (SL) is the most important communication way betweenhearing-impaired community and normal persons. However, it is very common thatthe normal person does not know the SL. Thus, for assisting the hearing-impairedcommunity to communicate in aworld of spoken languages, there is a need to developa translation tool to assist the communication between hearing-impaired communityand normal persons.One of the translation tools available nowadays isHearingAssis-tive Technology (HAT). HAT can dramatically improve the communication withhearing problem and increase the sustainability of social interaction in community.This paper presents an approach of HAT in the development of the sign languagetranslation application for hearing-impaired communication by translating the SLgesture into a textual and audio form. This application integrates with a MicrosoftKinect Camera Sensor to detect the gesture of SL that is performed by the user whostands in front of the device. The SL translation application implements DynamicTime Warping (DTW) algorithm. It measures the similarity between two sequences,which was the recorded gesture stored in text file and the current gesture performedby the user. This paper evaluates the application using a user acceptance test basedon Technology Acceptance Model (TAM) that involved thirty (30) respondents todetermine the effectiveness of the system. The evaluation shows that most of theparticipants positively accepted the proposed application. Therefore, this applica-tion provides insight on the role of HAT which has prepared opportunities for thehearing-impaired and normal person to compensate and empower the communicationby using an automatic SL translation application.

M. N. Osman (B) · K. A. Sedek · N. Z. M. Zain · M. A. N. A. KarimUniveriti Teknologi MARA, Perlis Branch, 02600 Arau, Perlis, Malaysiae-mail: mohdnizam@uitm.edu.my

K. A. Sedeke-mail: khairulanwarsedek@uitm.edu.my

N. Z. M. Zaine-mail: nurzaid@uitm.edu.my

M. MaghribiPoliteknik Tuanku Syed Sirajuddin, 02600 Arau, Perlis, Malaysia

© Springer Nature Singapore Pte Ltd. 2020N. Z. Alias and R. Yusof (eds.), Charting the Sustainable Future of ASEANin Science and Technology, https://doi.org/10.1007/978-981-15-3434-8_1

1

2 M. N. Osman et al.

Keywords Hearing assistive technology · Hearing-impaired · Sign language ·Dynamic time warping · User acceptance test

1.1 Introduction

Assistive Technology (AT) was the term created by the IT people which refer to adevice or solution which mostly contribute to the disability community or peoplewith deficits, whether in physical, mental, or even emotional functioning (LaPlante1992; Shinohara and Wobbrock 2011). For many years, there were hundreds or evenmore assistive devices are available such as hearing-impaired devices, which helpthose people who have hearing problem and wheelchair is provided for those whocannot walk. Pollack (2005) stated that AT can also provide secure assurance to olderpeople by assisting their daily activities and can give alert status to their caretakerin case something happens to the older people. Besides, AT plays an importantrole in helping the person with disabilities to become more socially included andindependent (Kbar et al. 2017). Moreover, AT can also empower people to work andbecome more socialized in their daily life (Shinoharaand Wobbrock 2011).

In Malaysia, it is estimated that more than 30,000 hearing-impaired people inthe year 2016 are registered with the Jabatan Kebajikan Masyarakat (JKM) (2016).Through this statistic, it shows the importance of learning sign language as this isthe only language that was used as a communication. Unfortunately, sign languageis not compulsory for Malaysian people during the school time, making most of thepeople lack knowledge in the sign language. Besides, sign language also is one of thelanguages that is hard to learn (Joseph 2003) which required a lot of commitmentsto learn and consume a lot of time. Moreover, lack of knowledge in sign languagecan lead to miscommunication between the hearing-impaired person and the normalperson. A study by UNICEF stated that the lack of knowledge also can lead tostigma against people with disability, and they also feel discriminated by the society(UNICEF Malaysia 2017).

Nowadays, modern hearing aid technology can help and support the hearing-impaired community. Many devices or tools were used for alerting, telecommuni-cation, learning, playing, working, and listening in order to assist people with thehearing loss problem. For instance, hearing aid microphone with digital wirelesstechnology together with the digital signal processing algorithm will improve thehearing aid used by the user (Edward et al. 2012). Besides, the gesture technologywill create a better opportunity for the disabled people such as hearing-impaired asthis technology can assist in their daily life (Sharma and Droch 2015) because it iseasy to use and learn.

Meanwhile, the development of sign language application has grown rapidlyaround the world to support the hearing-impaired community. In Malaysia, a web-based learning course for teaching Malaysian sign language was developed and canbe accessed by the users without cost. This website implements multimedia elementssuch as graphic and animation to represent the letters of the alphabet and numbers in

1 Hearing Assistive Technology: Sign Language Translation … 3

sign language (Mokhtar and Anuar 2015). On the other hand, the application basedonAndroid to support deaf people by using speech-to-image conversation was devel-oped by Abdallah and Fayyoumi. This application was divided into several parts forlearning, playing, and translating the text into sign language and benefits the normalpersons to improve the communication with deaf people even though they have zeroknowledge in sign language (Abdallah and Fayyoumi 2016).

In order to get better understanding with sign language, which is a languagebeing used by the hearing-impaired or the disability people, a translation would bevery helpful as it can help to improve the communication and social interactionskill between the normal and hearing-impaired people. Therefore, the sign languagetranslation application using kinetic camera sensor was proposed to support thecommunication between normal people and hearing-impaired community. The mainpurpose of the sign language translation application is to translate the hand gestureand convert it into a textual and audio form, which will help the communication andinteraction skill, benefiting the normal and hearing-impaired community.

In this paper, the main sections are organized as follows: Sect. 1.2 provides themethodology of the proposed work. Section 1.3 discusses the result based on thetesting and evaluation conducted. Finally, Sect. 1.4 concludes the paper.

1.2 Methodology

1.2.1 Developing the System Architecture for Sign LanguageTranslation Application

Figure 1.1 illustrates the system architecture for the sign language translation appli-cation using kinetic camera sensor. Basically, the system consists of kinetic camerasensor, computer to run the sign language translation application, and a web serverto store database. Besides, the system involved two types of users. The first userrepresents the hearing-impaired person, who will stand in front of the kinetic camerasensor and perform the gesture of the sign language. Meanwhile, the second userwas a normal person, one who is running the application.

Once the kinetic camera sensor is connected to the computer and run the applica-tion, the interface of the application acts as a link between hearing-impaired person,kinetic camera, database, and normal person. Meanwhile, the dynamic time warpingalgorithm was implemented to compare the sequences which was the recorded ges-ture in the database and currently performed gesture and then the similarity betweensequences was measured. If the comparison was successful, the audio and text repre-senting the gesture performedby the hearing-impaired personwill be shown.Besides,the normal person also can record the new gesture to represent the sign language andstore it in the database.

4 M. N. Osman et al.

Fig. 1.1 System architecture of sign language translation application

1.2.2 Model Used for the Development of Sign LanguageTranslation Application

The Waterfall Model was used to develop the proposed application. The WaterfallModel emphasizes that a logical progression of steps be taken throughout the Soft-ware Development Life Cycle (SDLC) (Bassil 2012). In a Waterfall Model, eachphase must be completed before the next phase can begin and there is no overlap-ping in the phases. Figure 1.2 illustrates the Waterfall Model software developmentprocess.

Requirement Analysis: This is the most important phase (Kazim 2017) whichfocused on gathering all information that is needed for the project development. Inthis phase, all information, data, and problem statement were identified by readingarticles, journal, and thesis fromprevious research.On top of that, the current technol-ogy was observed in order to understand how technology can be implemented duringthe project development. Furthermore, the activities included were the identificationof hardware and software requirement, objectives, scope of project, schedule of activ-ities such as Gantt chart, and the total budget. The result of this phase is feasibilityreport and a logical system design.

Design: The logical system design from the previous phase was converted intophysical systemdesign. In this phase, the researcher designed the requirement neededin the system development. It implicates several tools and techniques for a solu-tion which included the system components, system architecture, conceptual design,database conceptual scheme, flowchart, and storyboard. Besides, the main focuseson the interfaces of the system were designed and the flow of the application was

1 Hearing Assistive Technology: Sign Language Translation … 5

Fig. 1.2 The waterfall model phases

identified. Basically, the application has two options, which is translation and capturenew gesture. Figure 1.3 shows the flow of the application.

Development: The application was developed using Microsoft Visual Studio,Notepad++, and C#. Skeleton algorithm was used in the application to producethe skeletal algorithm of the user who stands in front of the kinetic camera sensorto capture the coordinate of the sign language performed by the hearing-impairedperson. Then, the Dynamic Time Warping Algorithm (DTW) was implemented tocompare two sequences, which are the gesture performed by the hearing-impairedperson and the text file gesture recorded in the database. DTW was an algorithm

Start

User choose the available option

Option 1 Translation Kinetic Camera Sensor Activate Capturing Gesture Check Gesture

from the Library

Convert into Textual and Audio

form

Capture New

Gesture

Kinetic Camera Sensor Activate Capturing Gesture Edit Text File of

the GestureSave into Library

application

Output of the textual and audio form

Option 2

End

True

False

True

False

Fig. 1.3 The flow of the application

6 M. N. Osman et al.

used for pattern matching, a database of predefined gestures of each performed at aprevious time is stored (Ahmed et al. 2016).

The application has two options from which the user can choose either the trans-lation or adding a new gesture into the database. The translation option will activatethe kinetic camera sensor, and the hearing-impaired person needs to stand in front ofthe camera to capture the coordinate of the sign language. If the gesture is performedcorrectly, the application will display the text represented for the gesture performed,respectively. Besides, the application also has a speech synthesizer to pronounce thetext of the respective gestures. Meanwhile, the second option will add and define thenew sign language coordinate into the database. The user needs to save the coordinatein the text file format on the designated path location.

Evaluation: The application was tested whether it meets the requirements ofthe users. The application was evaluated to determine the system effectiveness byconducting a user acceptance test based on Technology Acceptance Model (TAM)(Venkatesh and Bala 2008) toward the target respondents to ensure that the respon-dents can perform the tasks, respectively. The target respondents of this study werethe normal people.

A quantitative approach was implemented in data collection based on a set of thesurvey questionnaire. A total of thirty (30) survey questionnaires were distributedand received for the analysis. The questionnaire consists of thirteen (13) questionsand categorized into four (4) parts. The first part comprised of the perceived easeof use, the second part is focused on the perceived usefulness, and the third part isabout attitude. Finally, the fourth part investigates the intention to use. The data wasanalyzed using arithmetic mean technique based on the ranking score value. Then,overall mean was calculated and classified into three categories, namely, negative,neutral, and positive based on the range of mean value between zeros to five as shownin Table 1.1.

Maintenance: After evaluation phase, minor refinement was done to integratecorrections of bugs and the user’s feedback which was focused mainly on fine-tuningof system, configuring, installing, and usability issues. It must meet the scope of anyfuture enhancement, future functionality, and any other added functional features tocope up with the latest needs.

Table 1.1 Range of meanvalue

Category Range of mean

Negative 0.00–1.66

Neutral 1.67–3.33

Positive 3.34–5.00

1 Hearing Assistive Technology: Sign Language Translation … 7

1.3 Results and Discussion

1.3.1 Interfaces of the Sign Language TranslationApplication

This section explains about the interfaces of the proposed application. Once thekinetic camera sensor is connected to the computer and the application runs, themaininterface of the application will be loaded as shown in Fig. 1.4a. This applicationwill be run by two types of users, which is the normal person who is running theapplication and hearing-impaired person,whowill stand in front of the kinetic camerasensor and performs the sign language gesture. In order to let the application detectwhat gesture has been performed by the hearing-impaired person, the normal personmust first upload the file by clicking the “Load Gesture File” button. There are twotypes of view, which is the view of the skeletal algorithm in which the user stands infront of kinetic camera sensor, while on the second view the camera is in the normalview, so that the user can see clearly on what the gesture has been performed.

To perform the sign gesture, the hearing-impaired person must stand in front ofthe kinetic camera sensor. If the gesture is performed correctly, it will show the text ofsign gesture that has been performed. Besides, the application also has a speech syn-thesizer where it will pronounce the text of the sign gesture performed, respectively.Moreover, this application also has the function to record and define a new gesture ofsign language. This function can be performed by clicking the “Capture” button andthe application will capture the gesture performed by the hearing-impaired person.Then, the user needs to click the “Save to File” button to save in the text file format.

Meanwhile, Fig. 1.4b summarizes the button included within the application. Thefunction of the button is given as follows:

READ/STORE: Read/Store mode button is an indicator which shows whetherthe application is in read mode or the new coordinate gesture of sign language isready to save in the file (Fig. 1.4).

CAPTURE: Capture the new gesture of sign language performed by the user.LOAD GESTURE FILE: Upload the recorded gesture file. Inside the text file

contains the coordinate of the recorded sign language. The dynamic time warpingalgorithm was implemented in this application where it will compare two sequences,which was the recorded gesture in the database and current gesture performed by thehearing-impaired person to measure the similarity between the two sequences.

SAVE TO FILE: Save a new gesture of sign language in the text file format.

1.3.2 User Acceptance Test

Toevaluate the user acceptance test on sign language translation application, the studywas tested to thirty (30) respondents. The experiment was conducted by giving therespondents opportunity to use and explore the system independently. Then theywere

8 M. N. Osman et al.

Fig. 1.4 Interface of the application in a main interface and b button

required to answer a set of questionnaires, which consist of thirteen (13) questionsand divided into several categories. The study has successfully done to evaluatethe effectiveness of the application and categorized into four components, whichinclude perceived ease of use, perceived usefulness, attitude, and intention to use.The participants were required to rate the answer with the scale of 1–5, which wasstrongly disagree, disagree, neutral, agree, and strongly agree.

Table 1.2 summarizes the results for the identified criteria and total mean foreach category, respectively. The results showed that the target respondents weresatisfied and positively accepted all functionalities and features provided by the signlanguage translation application.This canbe indicatedby the totalmean results for thePerceived Ease of Use received (PEU) 4.02 and Perceived Usefulness (PU) received4.20, respectively. On the other side, most of the participants wanted to use the signlanguage translation application for communication and improve knowledge in thesign language based on the totalmean results obtained 4.20 forAttitude (AT) and 4.00for Intention to Use (ITU). Besides, the overall total mean for the user acceptancetest was 4.09 which means positive feedback from the participants. Therefore, thisindicates that the participants have accepted the sign language translation applicationas a tool to communicate between hearing-impaired person and normal person.

1.4 Conclusion

This paper which has presented gives some insight on user technology to constructthe application for the hearing-impaired person to communicate with the normalperson. This application was developed to detect and capture the gesture of the handperformed by hearing-impaired person. The application then translates it into textand audio form. In order to perform the task, the application was integrated withthe hardware called the Microsoft kinetic camera sensor to detect the sign language

1 Hearing Assistive Technology: Sign Language Translation … 9

Table 1.2 The user acceptance test results

No. Criteria Score (1–5) Mean Mean category

1 2 3 4 5

Part 1: perceived ease of use (PEU)

1 I found that AT: signlanguage translationapplication interfaces aresimple and memorable

0 1 0 19 10 4.3 Positive

2 I found that it is not thatcomplicated to use AT:sign language translationapplication

0 4 5 13 8 3.8 Positive

3 Performing sign languagegesture using AT: signlanguage translationapplication is very easy

0 2 7 13 8 3.9 Positive

4 I think that other normalpeople use AT: signlanguage translationapplication without anyproblem

0 2 8 11 9 3.9 Positive

5 Overall, AT: sign languagetranslation application easethe user to learn signlanguage

0 0 5 14 11 4.2 Positive

Total mean (PEU) 4.02 Positive

Part 2: perceived usefulness (PU)

6 AT: sign languagetranslation application canimprove my knowledgetoward sign language

0 3 2 13 12 4.1 Positive

7 AT: sign languagetranslation application canhelp meinteract/communicate withpeople who use signlanguage as theircommunication

0 0 1 17 12 4.4 Positive

8 AT: sign languagetranslation applicationmight be helpful for me tolearn sign language

2 0 1 20 7 4.0 Positive

Total mean (PU) 4.20 Positive

Part 3: attitude (AT)

(continued)

10 M. N. Osman et al.

Table 1.2 (continued)

No. Criteria Score (1–5) Mean Mean category

1 2 3 4 5

9 I like the idea of AT: signlanguage translationapplication

0 1 1 9 19 4.5 Positive

10 Generally, I wouldencourage my friends touse AT: sign languagetranslation application

0 4 2 10 14 4.1 Positive

11 I believe (would be) goodidea to use AT: signlanguage translationapplication to improvecommunication withhearing-impaired people

1 1 2 15 11 4.1 Positive

Total mean (AT) 4.20 Positive

Part 4: intention to use (ITU)

12 If I have the access to AT:sign language translationapplication, I would like touse it to help mecommunicate with thehearing-impaired people

2 0 6 9 13 4.0 Positive

13 AT: sign languagetranslation applicationwould be one of myfavorite applications toimprove knowledge in signlanguage

0 1 8 10 11 4.0 Positive

Total mean (ITU) 4.00 Positive

Overall total mean 4.09 Positive

gesture. Furthermore, the most advantageous of being supported by this applicationwas that it can easily record and define new gestures to be added into the database.The recorded gesture will be stored in the form of the text file format which containsthe coordinate of the gesture.

The application was measured using a user acceptance test based on the tech-nology acceptance model. This test was performed to see the acceptance of normalpersons toward the application. The questionnaire was divided into four (4) com-ponents. These components consisted of thirteen (13) questions. Thirty respondentsparticipated in the test. Most of the respondents were satisfied with the functional-ities provided by the application and found that it was a great idea to develop anapplication that focused on the sign language.

In conclusion, the sign language translation application using kinetic camera sen-sor was positively accepted by the users to assist the normal people to communicate

1 Hearing Assistive Technology: Sign Language Translation … 11

with the hearing-impaired person. Therefore, the use of hearing assistive technol-ogy can dramatically improve the lives of people with hearing loss and increasethe sustainability of social interaction skill between hearing-impaired and normalcommunity.

References

Abdallah EE, Fayyoumi E (2016) Assistive technology for deaf people based on android platform.Procedia Comput Sci 94:295–301

AhmedWet al (2016)Vision based hand gesture recognition using dynamic timewarping for Indiansign language. In: 2016 international conference on information science (ICIS), pp 120–125. IEEE

Bassil Y (2012) A simulation model for the waterfall software development life cycle. Int J EngTechnol 2(5):1–3

Edward AP et al (2012) Strategies for teaching learners with special needs. PearsonJabatanKebajikanMasyarakat (JKM) Laporan Statistik JabatanKebajikanMasyarakat 2016. http://www.jkm.gov.my/jkm/uploads/files/penerbitan/Bukustatistik2016.pdf. Accessed 8 Apr 2019

Joseph P (2003) A study on certain factors influencing language performance of hearing impairedstudents. Asia Pac Disabil Rehabil J 14(2):201–208

Kazim A (2017) A study of software development life cycle process models. 8(1):15–23Kbar G et al (2017) Assistive technologies for hearing, and speaking impaired people: a survey.Disabil Rehabil Assist Technol 12(1):3–20

LaPlante MP et al (1992) Assistive technology devices and home accessibility features: prevalence,payment, need, and trends. Advance data from vital and health statistics

Mokhtar SA, Anuar SMS (2015) Learning application forMalaysian sign language: content design,user interface and usability. In: Proceedings of the 9th international conference on ubiquitousinformation management and communication, pp 1–6. ACM, New York, NY, USA

Pollack ME (2005) Intelligent technology for an aging population: the use of AI to assist elderswith cognitive impairment. 26(2):9–24

Sharma V, Droch B (2015) Gesture-controlled user interfaces. J Inf Sci Comput Technol 2(1):133–135

Shinohara K, Wobbrock JO (2011) In the shadow of misperception: assistive technology use andsocial interactions. In: Proceedings of the SIGCHI conference on human factors in computingsystems, pp 705–714. ACM, New York, NY, USA

UNICEF Malaysia (2017) Childhood disability in MalaysiaVenkateshV, BalaH (2008) Technology acceptancemodel 3 and a research agenda on interventions.Decis Sci 39:273–315

Chapter 2Fish Freshness Detector Using SensoryQuality Index Method and Digital ImageProcessing Evaluation

Khairul Naim Abd.Aziz, Shameen Izwan Anthonysamy,Zamzila Erdawati Zainol, Muhammad Akmal Roslaniand Sharir Aizat Kamaruddin

Abstract Fish freshness detector (FFD) currently plays an important role in assess-ing fish for consumers. There are FFDs available out there in the market, but they arenot conveniently accessible by common users. Therefore, it is important to design anFFD that can deliver accurateness which can be adopted for its users to make instantpurchasing decisions. To achieve that, this paper proposed FFDmodel based on fuzzylogic as system, while Rastrelliger kanagurta andUmbrina roncador as fish samplesspecies for evaluation. The proposed model consists of two evaluation parts, sensoryquality index method (QIM) assessment and digital image processing. Both wereonly focusing on the fish eye, which a sensory assessment for QIM and the rednessvalue (RV) for the image processing. Based on distinct species evaluation againstdays of storage and condition after death, the eye sensory QIM for both species startsto change from clear to dull throughout 12 days in ice storage. R. kanagurta showeda rapid rate of deterioration compared to U. roncador. The RV distribution recordedranges between 81 and 129 for both species. Finally, a fish freshness indicator asinput setting in fuzzy logic inference system based on sensory QIM and RV weresuccessfully developed in this pilot test.

K. N. Abd.Aziz (B) · S. I. Anthonysamy · Z. E. Zainol ·M. A. Roslani · S. A. KamaruddinFaculty of Applied Sciences, Universiti Teknologi MARA, Perlis Branch, Arau Campus, Perlis,Malaysiae-mail: khairul87@uitm.edu.my

S. I. Anthonysamye-mail: shameenizwan@yahoo.com

Z. E. Zainole-mail: zamzila396@uitm.edu.my

M. A. Roslanie-mail: akmalroslani@uitm.edu.my

S. A. Kamaruddine-mail: shariraizat@uitm.edu.my

K. N. Abd.Aziz · Z. E. Zainol · M. A. Roslani · S. A. KamaruddinFaculty of Applied Sciences, Marine Research and Excellence Centre (MAREC), UniversitiTeknologi MARA, Perlis Branch, Arau Campus, Perlis, Malaysia

© Springer Nature Singapore Pte Ltd. 2020N. Z. Alias and R. Yusof (eds.), Charting the Sustainable Future of ASEANin Science and Technology, https://doi.org/10.1007/978-981-15-3434-8_2

13

14 K. N. Abd.Aziz et al.

Keywords Fish freshness · Quality index method · Fuzzy logic · Redness value

2.1 Introduction

A food is considered fresh when it is in a good and natural condition, as well as fishesare. As consumers, many usually have no clue on how long the fish displayed for saleespecially, in the supermarket. Some supermarket even puts old fish on their table,and consumers did not really get for what they have paid (Hakim et al. 2018; Shettyand Kumar 2016; Cheng et al. 2013). A slight misinterpretation of stale fish willresult in histamine fish poisoning. Consequently, consuming stale fish will increasehealth problems (Humaid and Mamdoh 2014).

The main factor of spoilage in fish is due to the activity of psychotropic gram-negative bacteria, such as Shewanella putrefaciens and Pseudomonas spp. Thosebacteria are commonly known as pathogenic bacteria, whereby it is transmittable tohuman via consumption. Pathogenic bacteria will multiply and cause infections afterit produces a type of toxins in the human body (Zad 2013).

Human interpretations are generally subjective, even for experienced and well-trained personnel. Common consumers hold less information to determine the fishfreshness and usually rely on experience in assuming based on low odor, moist flesh,sensory assessment and others. In sensory assessment for fish eye, consumers usuallyuse its redness as an indicator to predict whether the fish condition is fresh or stale.However, it is inaccurate and the information of assuming fish freshness varies fromone to another when compared to computers which are sensitive to wide range ofhigher and lower color frequencies (Hosseini et al. 2008; Kishore et al. 2016; Issacet al. 2017; Muhamad et al. 2009).

Addressing these issues, FFD has been introduced and established in the industryfor some time; however, most of the methods used to detect the freshness of the fishrequire a laboratory practice. There are also FFDs that require fishes’ sample, hencepromotes more bacteria spread. In addition, FFDs are generally expensive, time-consuming and not always available (Shetty and Kumar 2016; Chen et al. 2017;Dowlati et al. 2013; Elmasry et al. 2015).

The intention of this study is to design a sensory FFD based on digital imageprocessing. This pilot test system will enable users to interpret fish freshness withoutany contact to the samples. In achieving that, two objectives were outlined. It startedwith the classification of sensory quality index method (QIM) for fish freshness ondaily basis, followed by the extraction of redness value (RV) in fish eye against thedays of storage. The data gathered were used to develop a dedicated rule about thefish species in fuzzy logic inference application.

2 Fish Freshness Detector Using Sensory Quality Index Method … 15

2.2 Methodology

Aside from fresh water fish, marine fish were the most consumed fishes in peninsularMalaysia. The two samples used for this study were Indian mackerel; Rastrelingerkanagurta and Yellowfin croaker; Umbrina roncador, since those species are highlyconsumed and reasonably low price in the market (Hakim et al. 2018; Humaid andMamdoh 2014). The fish samples were taken directly from the fishermen to ensurethe freshness of the fish. It was to ensure that the fish samples were on its day 0 fromthe day it died.

The number of 10 samples for each species were tagged and stored in a separateinsulated cool box for 12 days. During the storage period, crushed ice was used andreplaced for every 3 days. The ice was layered in between and thoroughly mixed withthe samples, a thick layer (5 cm) around the sides, top and bottom of the container(Muhamad et al. 2009; Murakoshi et al. 2013). The process flow for this study is asshown in Fig. 2.1.

In acquiring the RV data, two stages were considered: the image acquisition andredness extraction. Acquisition of the image was carried out using a smartphonecamera, iPhone 5 equipped with a built-in 8-megapixels and 1136× 640 pixels. Thephotos were auto-saved in the smartphone’s library in JPEG format (Kishore et al.2016; Issac et al. 2017; Dowlati et al. 2013).

While for the extraction, the imagewas processed by cropping the fish eye segmentfrom the full-scale image obtained. The RV was analyzed using histogram extractedfrom ImageJ application. ImageJ will provide the image histogram that consists ofmean value, count, standard deviation andmode of the redness in 8-bit digital number0–255 range of interval. All data were scrutinized for attribute settings into fuzzylogic inference system.

Fresh Fish From

FishermanStorage

QIM Assessment

+ Image

Collection

Image Processing

Data Analysis

Fuzzy System Setup

Fig. 2.1 The process flow of fish freshness detector (FFD) using fuzzy logic system

16 K. N. Abd.Aziz et al.

QIM + RV Data Fuzzification

DefuzzificationFish Freshness

Fuzzy Inference System (FIS)

Fig. 2.2 The flowchart of fish freshness detector (FFD) using fuzzy logic system

Both fish sampleswere analyzed by using two different assessments, sensoryQIMand RV. For the sensory changes three parts of the eye, such as surface, eyeball andeye, were analyzed. The changes in eye characteristics were recorded accordinglyin the QIM form (Cheng et al. 2013; Murakoshi et al. 2013; Karagöz 2013). Theflowchart of the process from input to output for the proposed system is shown inFig. 2.2.

The system was set to a specified rule known as Mamdani fuzzy inference system(FIS) with two inputs (QIM score and RV) and one output (freshness by day). Allrecorded data from sensory QIM and RV were inserted into the FIS via membershipfunction (MF) in MATLAB R2015a software. At the end, the result would indicatethe specific day and freshness level of the fish sample. Each species was expected toyield out different reading especially in the RV; therefore each species needs differentdatabase and attribute settings in the FIS to produce an accurate output.

2.3 Findings

This study depicted the average value of sensory QIM scores and RV’s extraction ofsamples’ digital image. Table 2.1 shows the sensory QIM scores against the day ofstorage. The sensory QIM score starts to decrease as day increases for both species.Organoleptic and other study related to QIM also found that the longer the storage,the lower the average score of its quality (Hakim et al. 2018; Cheng et al. 2013;Kishore et al. 2016). The storage method chosen had impact on the samples too,without any preservatives fish deteriorates faster, and freshness condition changedrapidly.

2 Fish Freshness Detector Using Sensory Quality Index Method … 17

Table 2.1 The eye sensoryQIM freshness score and daysof storage for R. kanagurtaand U. roncador

Score Condition Day

0–1 Spoiled 12 and above

2 Very stale 10–12

3 Stale 4–9

4 Fresh 1–3

5 Extremely fresh 0

The QIM score sheet consists of three sensory features analyzed by the panel.Each feature has the same score range from 0 to 5. The lowest score of 0 indicatesthat the fish is at the highest level of damage, while the highest score of 5 indicatesthat the fish is in a extremely fresh state. Surface, eyeball and eye are the three sensoryfeatures that have been considered in this QIM analysis.

Comparing changes in the two species studied, R. kanagurta showed a slight dif-ference compared to U. roncador because both species had different eye anatomy.This study observed that U. roncador tends to have a narrower shape of pupilcompared to R. kanagurta which is round (Table 2.2).

At initial day 0, R. kanagurta possess a bulging with protruding lens; shiny blackpupil with metallic brown iris and a transparent eye lid. At day 3, the eye slightlycloudy, and wrinkles started to occur in the iris; clouding of eye cap. At day 6 theeye started to turn into a dull and brownish color. On day 9, most of the samples hadsunken and dull eyes covered with yellow slime. After day 12, the entire sampleswere getting opaque, dull and damaged eyes.

On the other hand for U. roncador, the eye of all samples was initially convex,very bright and iridescent oval pupil. At day 3, the eye was still clear but loss ofbrightness and slightly cloudy. Day 6 showed an obvious change such that there wasiridescence narrow pupil and the color of the eye started to become darker. At day 9onwards, the eye started to flatten and became opaque.

At day 12, the eye was already sunken, opaque and covered with yellow slime.This study found thatmost samples of both species showed dark and dull eyes coveredwith a clear jelly-like slime. This is due to bacterial infection produced by the fishonce it undergoes deterioration (Hakim et al. 2018; Humaid andMamdoh 2014; Dinget al. 2014). Unfortunately, toward the end of the observations neither R. kanagurtanor U. roncador fish portray a clearly bloody eye as expected. The observations areshown in Table 2.2.

In the extraction of RV from fish eyes, the red color band (brightest to the dark-est) interval was interpreted via pixel reading inside the yellow arc as in Table 2.2.The mean data recorded were roughly 81–129 and 85–125 for R. kanagurta andU. roncador, respectively, as the color of eye turned from clear to dark and dull.The presence of the uncertain red value distribution was likely due to photographicunforced errors. Even though these aspects can be minimized, it was hard to beeliminated completely (Issac et al. 2017; Muhamad et al. 2009; Chen et al. 2017;Murakoshi et al. 2013). The mean of RV of the samples against days of storage wasplotted in Fig. 2.3.

18 K. N. Abd.Aziz et al.

Table 2.2 Eye changes forsensory QIM assessmentwithin 12 days for both fish(R. kanagurta and U.roncador); samples werepatched with yellow arc forRV extraction

Day ofstorage

Fish species

R. kanagurta U. roncador

Day 0

Day 3

Day 6

Day 9

Day 12

Through the RV recorded, a smooth linear line was constructed to analyze the eyeredness. Figure 2.3 shows a different trend despite their similar scores in the freshnessby sensoryQIMassessment. In the period of 12 days,R. kanagurta followed the trendof the freshness level; however, for U. roncador the trend less likely agreed with thelevel of fish freshness recorded. The deterioration changes such as in opaqueness,

2 Fish Freshness Detector Using Sensory Quality Index Method … 19

1

2

3

4

5

40

60

80

100

120

140

0 2 4 6 8 10 12

QIM

Sco

re

Red

ness

Mea

n V

alue

Day

Rastrelliger Umbrina QIM

Linear (Rastrelliger) Linear (Umbrina )

Fig. 2.3 The scatter plot of RV and sensory QIM score of R. kanagurta and U. roncador againstdays of storage

cloudiness, shapes and conditions (sunken) of the fish eye also contribute to theuneven RV distribution.

In addition, the photographic unforced errors which derived from the luminanceand translucency were also a leading factor toward the RV distribution. The wetnessthat derived from different eye fluid concentration as fishwent along the deteriorationaffects the way of light reflected and refracted. Apart from that, the reflection andrefraction properties also differwith temperature and humidity content, thus affectingon the digital image taken (Muhamad et al. 2009; Murakoshi et al. 2013). Besides,bloody red color in the fish eye may sometimes be fresh fish but mishandling whentransported or many other factors had caused the blood capillary ruptures (Hakimet al. 2018; Humaid and Mamdoh 2014).

The FIS settings as the main aim of this study were developed based on sen-sory QIM and RV data gathered. The input for RV in the system was set into therange according to the species sampled, R. kanagurta and U. roncador, respectively.Figure 2.4 shows the surface view of rules from MF that had been set into the FISfor fish freshness detection.

There were three MFs set into the variable, which were low, medium and high.This would help for easier identification of the value on RV related to the fish oncertain conditions. Those values set were based on the sensory QIM scores. Theoutput in the system was then set into day of the fish freshness. For that output,four MF plots were set to differentiate freshness status of the fish. They were knownas extremely fresh, fresh, stale and spoilt respectively, within the day range of 0–12 days. Finally, using this setting, once an image captures, the FFD will inform itsuser the condition of fish by their day after caught and their freshness.

20 K. N. Abd.Aziz et al.

Fig. 2.4 The surface view of rules settings for fish freshness detection (FFD) with sensory QIMand RV input of a R. kanagurta and b U. roncador

2 Fish Freshness Detector Using Sensory Quality Index Method … 21

2.4 Conclusion and Recommendations

The quality and freshness of the fish begin to deteriorate as soon as the fish diesand cannot be stopped but it can only be delayed. The combined stimulus of timeof death, temperature, environment and method of storage had proven to enhancethe effect of the fish deterioration. This study found that the change in reading ofred value (RV) in both fish eye samples was in the range of 80–130 within 12 days.Apart from that, a freshness indicator for R. kanagurta andU. roncador fish based onsensory QIM and RV were successfully developed. However, each species recordeda slight difference reading especially in their RV; therefore each species needs adifferent database and attribute settings to produce an accurate output. Overall, thispilot test on developing FFD based on image processing was capable of producinga convincing result to assist consumers or common users for instant fish purchasingdecisions.

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Ding R, Huang X, Han F, Dai H, Teye E, Xu F (2014) Rapid and nondestructive evaluation of fishfreshness by near infrared reflectance spectroscopy combined with chemometrics analysis. AnalMethods 6:9675–9683

Dowlati M, Saeid S, Omid M, Hadi S, Jamzad M, De M (2013) Freshness assessment of giltheadsea bream (Sparus aurata) by machine vision based on gill and eye color changes. J Food Eng119(2):277–287

Elmasry G, Nagai H, Moria K, Nakazawa N, Tsuta M, Sugiyama J, Okizaki E, Nakauchi S (2015)Freshness estimation of intact frozen fish using fluorescence spectroscopy and chemometrics ofexcitation-emission matrix. Talanta 143:145–156

Hakim G, Liviawaty E, Hasan Z (2018) Study of freshness of Mackerel (Rastrelliger kanagurta(Cuvier, 1816)) at Rancaekek Market, Resik Market, and Tanjungsari Market. World Sci News114:1–14

Hosseini HG, Luo D, Xu G, Liu H, Benjamin D (2008) Intelligent fish freshness assessment. JSensors 2008:8

Humaid SA,Mamdoh TJ (2014) Effect of storage temperature on histamine formation and bacterialgrowth in whole three fish species (Rastrelliger kanagurta, Sardinella gibbosa and Lethrinuslentjan). Life Sci J 11(9):927–937

Issac A, KishoreM, Sarkar B (2017) Computer vision basedmethod for quality and freshness checkfor fish from segmented gills. Comput Electron Agric 139:10–21

Karagöz A (2013) Fish freshness detection by digital fish freshness detection by digital imageprocessing. Dokuz Eylül University

Kishore M, Issac A, Minhas N, Sarkar B (2016) Image processing based method to assess fishquality and freshness. J Food Eng 177:50–58