Editor-In-Chief Chair Dr. Shiv Kumar

Ph.D. (CSE), M.Tech. (IT, Honors), B.Tech. (IT), Senior Member of IEEE, Member of the Elsevier Advisory Panel

CEO, Blue Eyes Intelligence Engineering & Sciences Publication, Bhopal (M.P.), India

Additional Director, Technocrats Institute of Technology and Science, Bhopal (MP), India

Associated Editor-In-Chief Members Dr. Hitesh Kumar

Ph.D.(ME), M.E.(ME), B.E. (ME)

Professor and Head, Department of Mechanical Engineering, Technocrats Institute of Technology, Bhopal (MP), India

Dr. Gamal Abd El-Nasser Ahmed Mohamed Said

Ph.D(CSE), MS(CSE), BSc(EE)

Department of Computer and Information Technology , Port Training Institute, Arab Academy for Science, Technology and Maritime

Transport, Egypt

Associated Editor-In-Chief Members Dr. Mayank Singh

PDF (Purs), Ph.D(CSE), ME(Software Engineering), BE(CSE), SMACM, MIEEE, LMCSI, SMIACSIT

Department of Electrical, Electronic and Computer Engineering, School of Engineering, Howard College, University of KwaZulu-

Natal, Durban, South Africa.

Scientific Editors Prof. (Dr.) Hamid Saremi

Vice Chancellor of Islamic Azad University of Iran, Quchan Branch, Quchan-Iran

Dr. Moinuddin Sarker

Vice President of Research & Development, Head of Science Team, Natural State Research, Inc., 37 Brown House Road (2nd Floor)

Stamford, USA.

Dr. Fadiya Samson Oluwaseun

Assistant Professor, Girne American University, as a Lecturer & International Admission Officer (African Region) Girne, Northern

Cyprus, Turkey.

Dr. Robert Brian Smith

International Development Assistance Consultant, Department of AEC Consultants Pty Ltd, AEC Consultants Pty Ltd, Macquarie Centre, North Ryde, New South Wales, Australia

Dr. Durgesh Mishra

Professor (CSE) and Director, Microsoft Innovation Centre, Sri Aurobindo Institute of Technology, Indore, Madhya Pradesh India

Executive Editor Dr. Deepak Garg

Professor, Department Of Computer Science And Engineering, Bennett University, Times Group, Greater Noida (UP), India

Executive Editor Members Dr. Vahid Nourani

Professor, Faculty of Civil Engineering, University of Tabriz, Iran.

Dr. Saber Mohamed Abd-Allah

Associate Professor, Department of Biochemistry, Shanghai Institute of Biochemistry and Cell Biology, Shanghai, China.

Dr. Xiaoguang Yue

Associate Professor, Department of Computer and Information, Southwest Forestry University, Kunming (Yunnan), China.

Dr. Labib Francis Gergis Rofaiel

Associate Professor, Department of Digital Communications and Electronics, Misr Academy for Engineering and Technology,

Mansoura, Egypt.

Dr. Hugo A.F.A. Santos

ICES, Institute for Computational Engineering and Sciences, The University of Texas, Austin, USA.

Dr. Sunandan Bhunia

Associate Professor & Head, Department of Electronics & Communication Engineering, Haldia Institute of Technology, Haldia

(Bengal), India.

Technical Program Committee Dr. Mohd. Nazri Ismail

Associate Professor, Department of System and Networking, University of Kuala (UniKL), Kuala Lumpur, Malaysia.

Technical Program Committee Members Dr. Haw Su Cheng

Faculty of Information Technology, Multimedia University (MMU), Jalan Multimedia (Cyberjaya), Malaysia.

Dr. Hasan. A. M Al Dabbas

Chairperson, Vice Dean Faculty of Engineering, Department of Mechanical Engineering, Philadelphia University, Amman, Jordan.

Dr. Gabil Adilov

Professor, Department of Mathematics, Akdeniz University, Konyaaltı/Antalya, Turkey.

Manager Chair Mr. Jitendra Kumar Sen

Blue Eyes Intelligence Engineering & Sciences Publication, Bhopal (M.P.), India

Editorial Chair Dr. Arun Murlidhar Ingle

Director, Padmashree Dr. Vithalrao Vikhe Patil Foundation’s Institute of Business Management and Rural Development, Ahmednagar

(Maharashtra) India.

Editorial Members Dr. J. Gladson Maria Britto

Professor, Department of Computer Science & Engineering, Malla Reddy College of Engineering, Secunderabad (Telangana), India.

Dr. Wameedh Riyadh Abdul-Adheem

Academic Lecturer, Almamoon University College/Engineering of Electrical Power Techniques, Baghdad, Iraq

Dr. S. Brilly Sangeetha

Associate Professor & Principal, Department of Computer Science and Engineering, IES College of Engineering, Thrissur (Kerala),

India

Dr. Issa Atoum

Assistant Professor, Chairman of Software Engineering, Faculty of Information Technology, The World Islamic Sciences & Education University, Amman- Jordan

Dr. Umar Lawal Aliyu

Lecturer, Department of Management, Texila American University Guyana USA.

Dr. K. Kannan

Professor & Head, Department of IT, Adhiparasakthi College of Engineering, Kalavai, Vellore, (Tamilnadu), India

Dr. Mohammad Mahdi Mansouri

Associate Professor, Department of High Voltage Substation Design & Development, Yazd Regional Electric Co., Yazd Province,

Iran.

Dr. Kaushik Pal

Youngest Scientist Faculty Fellow (Independent Researcher), (Physicist & Nano Technologist), Suite.108 Wuhan University, Hubei,

Republic of China.

Dr. Wan Aezwani Wan Abu Bakar

Lecturer, Faculty of Informatics & Computing, Universiti Sultan Zainal Abidin (Uni SZA), Terengganu, Malaysia.

Dr. P. Sumitra

Professor, Vivekanandha College of Arts and Sciences for Women (Autonomous), Elayampalayam, Namakkal (DT), Tiruchengode

(Tamil Nadu), India.

Dr. S. Devikala Rameshbabu

Principal & Professor, Department of Electronics and Electrical Engineering, Bharath College of Engineering and Technology for

Women Kadapa, (Andra Pradesh), India.

Dr. V. Lakshman Narayana

Associate Professor, Department of Computer Science and Engineering, Vignan’s Nirula Institute of Technology & Science for

women, Guntur, (Andra Pradesh), India.

S. NoVolume-9 Issue-4S, May 2020, ISSN: 2249-8958 (Online)

Published By: Blue Eyes Intelligence Engineering & Sciences Publication Page No.

1.

Authors: Amala Benny, Neethu Suman

Paper Title: ADMS-Automatic Diabetic Management System

Abstract: Diabetes could be a common chronic disease in mostly all countries worldwide. Monitoring ofglucose level of blood is vital to avoid complications of diabetic and damage to organs. The most commonlyused method to live glucose level in blood is an invasive method which is painful, expensive and danger inspreading infectious diseases. Over an extended term, the invasive method results in damage of finger tissues.The proposed system works on a diabetes patient, and gives information about patient condition to patient careror observer. Patient’s fingertip is placed between the glucose measuring sensors that measure glucose valuethrough the help of microcontroller. If the glucose level is increased insulin injector will automatically inject theinsulin in the body and if it is decreased glucose is injected. Patient’s mobile application use to see glucosemeasurement at each time and also the injected glucose and insulin amount. In critical condition, sms containingvital information and location are sent to doctor or relative’s phone.

Keyword: Continuous Glucose Monitoring System, Diabetic Management System, Wireless Body AreaNetwork.

References:

1. Ganjar Alfian, Muhammad Syafrudin, Muhammad Fazal Ijaz,M. Alex Syaekhoni, Norma LatifFitriyani and Jongtae Rhee, A Personalized Healthcare Monitoring System for Diabetic Patients byUtilizing BLE-Based Sensors and Real-Time Data Processing, 2018 Jul; 18(7): 2183. Published online2018 Jul 6. doi:10.3390/s18072183

2. A. Dearden, P. Wright, S. Bowen, F. Rahman, M. Cobb, D. Wolstenholme, Pervasive healthcare inlived experience: thinking beyond the home, in Procceedings of the 4th International ICST Conferenceon Pervasive Computer Technology and Healthcare, (2010), pp. 1–4H.

3. Lee, K. Park, B. Lee, Issues in data fusion for healthcare monitoring in Issues in Data Fusion forHealthcare Monitoring, no. Jan 2008 (2013)

4. C. Chen, X. Zhao, Z. Li, Z. Zhu, S. Qian, A.J. Flewitt, Current and emerging technology for continuousglucose monitoring. Sensors 17(1), 182 (2017)

5. Dexcom Inc., Dexcom and Insulin Pumps. [Online].https://www.dexcom.com/insulinpumps. Accessed27 Dec 2017

6. Minimed 670G from Medtronic Inc https://www.medtronicdiabetes.com/products/minimed670ginsulin-pump-system.

7. FreestyleLibre Flash from Abbott Diabetes Care https://www.freestylelibre.us/index.html. 8. Pop Test LLC, Glucose Pop TEST. [Online]. http://www.diabetespoptest.com/. Accessed 30 Dec 2017. 9. LLC Quick, IQuickIt Saliva Analyzer (LLC Quick, Farmington, CT). 10. Light Touch Medical Inc., Ocular Glucose Monitor. [Online]. Available: http://tearglucose.com/.

Accessed 30 Dec 2017 11. J.T. LaBelle, Tear TOUCH Glucose Sensing. [Online]. http://labellelab.asu.edu/research/touch/.

Accessed 30 Dec 2017 12. C. Bernal, GlucosAlarm. [Online]. http://www.glucosalarm.com/. Accessed 30 Dec 2018 13. H. Lee, C. Song, Y.S. Hong, M.S. Kim, H.R. Cho, T. Kang, K. Shin, S.H. Choi, T. Hyeon,D.-H. Kim,

Wearable/disposable sweat-based glucose monitoring device with multistage transdermal drug deliverymodule. Sci. Adv. 3(3), e1601314 (2017)

14. Chandrakant D. Bobade, Dr. Mahadev S. Patil, “Non-Invasive Monitoring of Glucose Level in Bloodusing Near-Infrared Spectroscopy” International Journal of Recent Trends in Engineering & Research(IJRTER), Volume 02, Issue 06; June - 2016 [ISSN: 2455-1457

15. Md. Mahbub Alam, Swapnil Saha, Proshib Saha, Fernaz Narin Nur,Nazmun Nessa Moon, Asif Karimand Sami Azam “D-CARE: A Non-invasive Glucose Measuring Technique for Monitoring DiabetesPatients, Proceedings of International Joint Conference on Computational Intelligence Pp. 443-453.

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2. Authors: Rohit N Nair, Prasanth P Menon, Roy Baiju, Sreelakshmi L S, V Kavyalakshmi

Paper Title: Multi Terrain Surveillance Drone

Abstract: The purpose of this research paper is to design a drone which can move autonomously in a fixedpredetermined route or by using radio waves through any environment. Various drones are available nowadayswhich differ in size, color and properties. Unmanned aerial vehicles have gained wide popularity over decadesand are used extensively for several applications. The main feature of this drone is that it does not require anyadditional infrastructure to quickly register and monitor the object. The major motive is to get accuracy in rescuemissions for accidents occurring at higher terrain as well as underwater. The main uniqueness is that it can movethrough air and water. An efficient algorithm is incorporated to reduce the complexity. The drone’s database is

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developed using artificial intelligence which helps in faster recognition of the object.

Keyword: drone; environment; AI; algorithm

References:

1. Nahid Mahamud, Galib Muhammad Shahriar; “ALW drone: A new design and efficient approach”, in [19th InternationalConference on Computer and Information Technology (ICCIT)], 2017 © IEEE

2. Chandykunju Alex, Aditya Vijaychandra; “Autonomous Cloud Based Drone System for disaster response and Mitigation”, in[International Conference on Robotics and Automation for Humanitarian Applications (RAHA)], 2016 © IEEE

3. Juan A. Besada, Ana M. Bernardos; “Drones-as-a-service: A management architecture to provide mission planning, resourcebrokerage and operation support for fleets of drones”,in [IEEE International Conference on Pervasive Computing andCommunications Workshops (PerCom Workshops)] 2019 © IEEE

4. Nguyen Dinh Dung, Jozsef Rohacs; “The drone-following models in smart cities”, [ 59th International Scientific Conference onPower and Electrical Engineering of Riga Technical University (RTUCON)] 2019 © IEEE

5. David Schneider; “Air traffic control for delivery drones”, in[IEEE Spectrum(Volume: 54, Issue:1 , January)] 2017 © IEEE

3.

Authors: P.K.Sisira, N.Aswathy, B. Prameela, Anju George

Paper Title: Ternary Content Addressable Memory

Abstract: Memory Technology plays a vital role in fast searching applications. Content Addressable Memory(CAM) is a special type of memory used for search operation. CAM provides access to the stored data by itscontent instead of the address. Advanced version of CAM is known as Ternary CAM (TCAM) which is amemory that can also store don’t care bit. TCAM is most relevant in routers in networking applications. Reviewof TCAM design techniques at different aspects are carried out, and obtained that an Energy Efficient TCAM(EE-TCAM) is the one which is having less power consumption. Compared with other SRAM-based TCAMdesigns, EE-TCAM use up reduced energy as it selectively activates only one row of SRAM at a time for searchoperation instead of activating the whole SRAM memory as in the other architectures. Partitioning of the TCAMtable, designing of a pre-classifier and memory mapping are done prior to the work. This paper focuses ondesigning an EE-TCAM using Verilog HDL on Zybo7000 platform using Vivado design suite. Functionalanalysis of a 6*6 EE-TCAM is performed and power, delay and resource utilization are obtained. From theobtained results it is clear that EE-TCAM is having very less power and delay.

Keyword: Memory, TCAM, EE TCAM, Pre-classifier

References:1. K. Pagiamtzis and A. Sheikholeslami, Content-Addressable Memory (CAM) Circuits and Architectures: A Tutorial and Survey,

IEEE Journal of Solid State Circuits, vol. 41, no. 3, pp.712-727, March 2006. 2. Zahid Ullah, Manish Kumar Jaiswal, Y.C. Chan,and Ray C.C. Cheung, “FPGA Implementation of SRAM-based Ternary Content

Addressable Memory”, 26th International Parallel and Distributed Processing Symposium Workshops PhD Forum,2012 3. Ullah Zahid, “SRAM-Based Ternary Content Addressable Memory”, Doctor of Philosophy City University of Hong Kong,

August 2014 . 4. Mahoney, P., Savaria. Y., Bois, G., and Plante, P., “Parallel Hashing Memories: an Alternative to Content Addressable

Memories”, 3rd International IEEE NEWCAS Conference, June 2005. 5. Madian Somasundaram, “Circuit to Generate a Sequential Index for an Input Number in a Pre-defined List of Numbers”, US

Patent, No. US 7155563 B1, December 2006. 6. Sangyeun Cho, Martin, J. R, Ruibin Xu, Hammoud, M. H, and Melhem, R, “CA -RAM: A High-Performance Memory Substrate

for Search-Intensive Applications”, proceedings of Performance Analysis of Systems Software, ISPASS, IEEE InternationalSymposium, April, 2007.

7. Ullah, Zahid. “LH-CAM: Logic-based higher performance binary CAM architecture on FPGA.” Embedded Systems Letters9.2,2017

8. Locke, K. Parameterizable content-addressable memory. In Xilinx Application Note XAPP1151; Xilinx: San Jose, CA, USA,2011.

9. Zahid Ullah and Sanghyeon Baeg, “Vertically Partitioned SRAM-based Ternary Content Addressable Memory,” ElsevierJournal, Procedia Engineering , 2011

10. Ullah, Z. Ilgon, K. Baeg, ”Hybrid partitioned SRAM-based ternary content addressable memory.” IEEE Trans. Circuits Syst. IRegul., 2012

11. Ullah, Z,Jaiswal, M.K. Cheung, R.C. “Z-TCAM: An SRAM-based architecture for TCAM.”, IEEE Trans. Very Large ScaleIntegr. Syst., 2015

12. Ullah, Z.,Jaiswal, M.,Cheung, R., “E-TCAM: An Efficient SRAM-Based Architecture for TCAM” Syst. Signal Process, 2014 13. Ullah, Z.; Jaiswal, M.K.; Cheung, R.C.C.; So, H.K.H. “UE-TCAM: An ultra efficient SRAM-based TCAM” In Proceedings of

the IEEE Region 10 Conference (TENCON) Macau, November 2015 14. Jiang, W. “Scalable ternary content addressable memory implementation using FPGAs”. In Proceedings of the Ninth ACM/IEEE

Symposium on Architectures for Networking and Communications Systems (ANCS), October 2013. 15. Ahmed, A.,Park, K. Baeg, S. “Resource Efficient SRAM-Based Ternary Content Addressable Memory”, IEEE Transaction on

Very Large Scale (VLSI) Integration Systems, April 2016 16. Inayat Ullah , Zahid Ullah and Jeong-A Lee,”EE- TCAM: An Energy-Effcient SRAM-Based TCAM on FPGA”,MDPI Journal of

Electronics,2018.

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4. Authors: Aiswarya Laskhmi T, Prajeesh P A, Adithya Sukumaran, Aswathy PA, Athira K K

Paper Title: Chlad Apock-Iot Based Security Lock Safety at Your Hands

Abstract: In today’s hectic schedule, it is obvious to forget to lock the doors or off the lights and then checkfor it frequently. Obsessive Compulsive Disorder(OCD) is an anxiety disorder in which some people haverecurring ,unwanted thoughts, ideas or sensations that make them feel driven to do something repetitively .OCDcan make it difficult for the people to perform everyday activities. This paper is all about modernising the

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conventional door lock and smart lighting system in order to help people. The product is solution to severaldifficulties faced by people experiencing .Here we use a leading edge technology namely mobile application forchecking the status of door and light. The uniqueness of this product relies on the fact that using newtechnologies along with old ones will result in an agile and more dynamic system. Furthermore, the biggestadvantage of the proposed system over existing ones is that it can be easily installed with minimal requirementof infrastructures and planning.

Keywords: doorlock,minimum infrastructure, Mobile application, OCD

References:

1. Adrian Ioan Lita et al., “Door automation system for smart home implementation,” in [ 2017 IEEE 23rd International Symposiumfor Design and Technology in Electronic Packaging (SIITME)], [2017] © [IEEE]. doi: [ 10.1109/SIITME.2017.8259925]

2. Vikram Puri and Anand Nayyar, “Real time smart home automation based on PIC microcontroller, Bluetooth and Androidtechnology”[ 2016 3rd International Conference on Computing for Sustainable Global Development (INDIACom)], [2016] ©[IEEE].

3. Meera Mathew and R S Divya, “Super secure door lock system for critical zones,” in[ 2017 International Conference onNetworks & Advances in Computational Technologies (NetACT)],[2017] © [IEEE]. doi : 10.1109/NETACT.2017.8076773

4. Chieh-An Lo ,Yutzu Lin,Chengchic Wu “Which Programming Language Should Students Learn First? A Comparison of Javaand Python,” in [2015 International Conference on Learning and Teaching in Computing and Engineering], [2015] ©[IEEE]. doi:10.1109/LaTiCE.2015.15

5. Abdallah Kassem, Sami El Murr, Georges Jamous, Elie Saad, Marybelle Geagea “A smart lock system using Wi-Fi security” in[2016 3rd International Conference on Advances in Computational Tools for Engineering Applications (ACTEA)], [2016]©[IEEE]. doi : 10.1109/ACTEA.2016.7560143

6. Charoen Vongchumyen , Pakorn Watanachaturaporn, Chompoonuch Jinjakam, Akkradach Watcharapupong,WatjanapongKasemsiri, Kiatnarong Tongprasert “Door lock system via web application” in [2017 International Electrical EngineeringCongress (iEECON)],[2017] ©[IEEE]. doi: 10.1109/IEECON.2017.8075909

7. R. S. Divya and Meera Mathew , “Survey on various door lock access control mechanisms” in [ 2017 International Conference onCircuit ,Power and Computing Technologies (ICCPCT)],[2017] ©[IEEE]. doi : 10.1109/ICCPCT.2017.8074187

8. Mehmet Akif Özçoban ,Oguz Tan, Aydin Akan “Analysis of frontal phase synchronization in OCD patients” in [2018 26thSignal Processing and Communications Applications Conference (SIU)],[2018] ©[IEEE]. doi : 10.1109/SIU.2018.8404465

5. Authors: Shahala Shanavas, Sneha Raju, Sreeganesh S., Sreejil B.Nair, Albins Paul

Paper Title: Modified Anpr using Neural Networks

Abstract: Number Plate Recognition is a mass observation technique which is used to identify the vehicles.The identification and acknowledgement of a vehicle license plate is a key method in the greater part ofapplications related to vehicle movement. Moreover, it is a very famous and dynamic research subject in thefield of image processing. Since every vehicle have a unique plate number, so if we have to perceive a specificvehicle we can utilize the license plate. The main objective of automatic vehicle number plate recognition is todesign an efficient automatic authorized vehicle identification system by using the number plate. It has threemodules namely license plate extraction, segmentation and recognition. . Different methods, techniques andalgorithms have been developed to detect and recognize license plates. Nevertheless, due to the license platecharacteristics that vary from one country to another in terms of numbering system, colours, language ofcharacters, fonts and size. Further investigations are still needed in this field in order to make the detection andrecognition process very efficient. Although this domain has been covered by a lot of researchers, variousexisting systems operate under well-defined and controlled conditions. For example, some frameworks requirecomplicated hardware to make good quality images or capture images from vehicles with very slow speed. Forthis reason the detection and recognition of number plates in different conditions and under several climaticvariations remains always difficult to realize with good results. For that, we present an automatic system fornumber plate detection and recognition based on convolutional neural networks. CNN has proved its robustnesseven with distorted, tilted and illuminated datasets.

Keyword: ANPR, Image processing, number plate recognition, character segmentation, convolutional neuralnetwork, character recognition.

References:

1. Surajit Das, Joydeep Mukherjee, “ Automatic License Plate Recognition Technique using Convolutional Neural Network”,International Journal of Computer Applications Volume 169 – No.4, July 2017.

2. Muhammad TahirQadri,MuhammadAsif,” Automatic number plate recognition system for vehicle identification using opticalcharacter recognition”, International Conference on Advances in Computing, Communication Control and Networking(ICACCCN2018)

3. Faizalpatel,JaiminiSolanki,VivekRajguru,AnkitSaxena”Recognition of Vechicle Number Plate Using Image processingTechnique” Advanced Emergency Medicine 2018

4. S. Stephy Golda Mercy, Dr. I. MuthulakshmiPG Scholar,“Automatic number plate recognition using connected componentanalysis algorithm”, International Journal For Technological Research In Engineering Volume 5, Issue 7, March-2018

5. Jiudong Yang, Jianping Li, “Application of deep convolution neural network “, International Centre for Wavelet Analysis and ItsApplications.

6. PrathameshKulkarni,AshishKhatri, PrateekBanga, Kushal Shah,” Automatic Number Plate Recognition (ANPR) System forIndian conditions ” .

7. TianmeiGuo, Jiwen Dong ,HenjianLiˈYunxingGao , “Simple Convolutional Neural Network on Image Classification”,Department of Computer Science and Technology Shandong Provincial Key Laboratory of Network based Intelligent ComputingUniversity of Jinan, Jinan, China,2017

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8. SaadAlbawi ,Tareq Abed Mohammed, Saad Al-Zawi, “Understanding of a Convolutional Neural Network”, Department ofComputer Engineering, Istanbul University, Turkey, Department of Electronic Engineering, Diyala University, 2017.

6.

Authors: Dennies Rocky, Aajin Roy, Anujith S, Eldho K Paul, Akas G Kamal

Paper Title:Comparative Study of LBPH and Haar features in Real Time Recognition Under Varying LightIntensities

Abstract: Face recognition is a commonly used biometric and has a wide range of applications. We used anaccess control system that integrates face recognition technology. This paper discusses two algorithms that havebeen used in the face detection, Haar features and Local Binary Patterns Histogram (LBPH). The experimentalset up is done in an open environment using OpenCV library. Comparative study has been made between thesetwo algorithms based on parameters like illumination and hit rate. For the testing, the same training set andsamples were used.

Keyword: Face recognition, Haar features, LBPH, OpenCV

References:

1. Paul Viola and Michael Jones, “Rapid Object Detection using a Boosted Cascade of Simple Features”,IEEE Computer SocietyConference on Computer Vision and Pattern Recognition 2001.

2. Snehal Humne and Prachi Sorte, “A Review on Face Recognition using Local Binary Pattern Algorithm”, International ResearchJournal of Engineering and Technology (IRJET), Volume: 05 Issue: 06, June-2018.

3. Kushsairy Kadir, Mohd Khairi Kamaruddin, Haidawati Nasir, Sairul I Safie and Zulkifli Abdul Kadir Bakti, “A ComparativeStudy between LBP and Haar-like features for Face Detection Using OpenCV ”,International Conference on EngineeringTechnology and Technopreneurship(ICE2T) 2014.

4. Songyan Ma and Lu Bai, “ A face detection algorithm based on Adaboost and new Haar like features”, International Conferenceon Software Engineering and Service Science (ICSESS), 2016.

5. R. Padilla, C. F. F. Costa Filho and M. G. F. Costa, “Evaluation of Haar Cascade Classifiers Designed for FaceDetection” ,International Journal of Computer, Electrical, Automation, Control and Information Engineering Vol:6, No:4, 2012.

6. Jie Zhu, Zhiqian Chen, “Real Time Face Detection System using Adaboost and Haar like Features ”International; Conference onInformation Science and Control Engineering, April 2015.

7. Ahonen, Timo, Abdenour Hadid, and Matti Pietikainen.“Face description with local binary patterns: Application to facerecognition.” IEEE transactions on pattern analysis and machine intelligence, 2006.

8. Özdil A. and Özbilen M. M., “A Survey on Comparison of Face Recognition Algorithms”, Application of Information andCommunication Technologies (AICT), IEEE 8th International Conference, 2014.

9. J. Chao W L, Ding J J, Liu J Z. “Facial expression recognition based on improved local binary pattern and class-regularizedlocality preserving projection”. Signal Processing, 2015.

10. Zheng Xiang, Hengliang Tan, Wienling Ye. “The excellent properties of dense gird-based HOG features on face recognitioncompare to gabor and LBP”,LNCS3021,2018.

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