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Volume1 Issues 11 from Nov- 2020
INTERNATIONAL REFEREED JOURNAL OF ENGINEERING SCIENCE ANDTECHNOLOGY www.irjest.com
IRJEST @ www.irjest.com
Dynamic Control of Welcoming Bot using Novel Arduino based Face detection and Recognition Santhosh .M1, Vignesh .K2, Seeshanth.C3
1-3 Dr.M.G.R. Educational and Research Institute .Chennai, tamilnadu.
Abstract— before Arduino is an open-source electronics programming platform based on easy-to-use hardware and
software for worldwide users. Many techniques can be used to overcome a face recognition, face detection and liquid crystal
display problems. In this paper we design, program and test Arduino module for automatic face detection and recognition.
Further; a robot is designed by interfacing LCD with Arduino module which acts as key tool to cut through the complex
tasks that emerge in digital image processing technology.
Keywords: Arduino, Face recognition, Face detection, Liquid crystal display, Design, Implementation, Testing
—————————— ——————————
1 INTRODUCTION
Researchers with a little or no technical background in
electronics and programming experience various problems
from everyday objects to complex scientific instruments.
Arduino programming language (based on Wiring), and the
Arduino Software (IDE)Processing have added up to an
incredible amount of accessible knowledge that can be of great
help to novices and experts alike. Arduino Uno, Arduino
Nano, and Arduino Pro Mini Boards inevitably have
revitalized the automation industry with their easy to use
platform functions. Arduino technology is forming a new
dimension by making complicated things look easier and
interesting. Since Arduino is a fast processing, easy interface,
low costs, highly reliable and affordable technology, it is
chosen for the present study. This paper provides a glimpse of
type of Arduino boards, working principles, software
implementation and their applications for face recognition
and face detection.
Face recognition
The face recognition problem two predominant approaches:
Geometric (feature based) and photometric (view based). The
former is based on the spatial configurations of facial features
such as the geometrical distances and angles between eyes,
nose and mouth locations and the latter is used to recover the
shape of an object from a number of images(gradient map)
taken under different lighting conditions.
Face Detection
For The face detection task involves three step processes via,
pre- processing, classification and localization. The pictures
are handled before they are taken care of into the network. All
the trimmed pictures are then rectified for lighting through
standard calculations. Neural organizations are actualized to
order the pictures as countenances. Different network
configurations are experimented to optimize the results. We
used the Mat lab neural network toolbox to perform this task.
The localization process uses the trained neural network to search
for faces in an image and if present localize them in a bounding
box. Figure 1 show the typical algorithm for Face detection
system.
2. Materials and methods
Materials
The hardware components used for face detection and face
recognition in Arduino,module:Arduino,, ,LCD Screen
(compatible with Hitachi HD44780 driver), pin headers to
solderto the LCD display pins,10k ohm potentiometer,220-ohm
resistor, hook-up, ,wires breadboard System (pc with
windows os) Web camera Speaker Visual studio 2008 Sql
server 2008.
The software programming includes COM+ component services,
a commitment to XML and object-oriented design, support for new web services protocols such as SOAP, WSDL, and UDDI,
etc.NET framework components are depicted in figure 2.
Volume1 Issues 11 from Nov- 2020
INTERNATIONAL REFEREED JOURNAL OF ENGINEERING SCIENCE ANDTECHNOLOGY www.irjest.com
IRJEST @ www.irjest.com
Fig.4Webcam connection with LCD and Arduino
Fig.2 .NET Framework into its system architectural components
Methods
Digital Image Processing
Digital Image Processing is the processing of images which
are digital in nature by a digital computer. Digital image
processing techniques are motivated by three major
applications. These include the improvement of pictorial
information for human perception, efficient storage and
transmission and the image processing for autonomous
machine application. Facial detection and recognition falls
within the machine vision application of digital image
processing.
A typical block diagram of Digital Image Processing is
shown in figure 3.
2.2.2Specifications of Webcam
The webcam is the main requirement for facial recognition.
The webcam and its connections with LCD and Arduino are
shown in figure 4.
Fig.3 A typical block diagram for the steps in Digital
Image Processing
Face Matcher is composed of face Recognition server which runs
face engine as a service application to identify faces from Oracle
database. Face matcher accepts data from any Smartphone, Media
Server, and Full- HD IP cameras through Axon Next protocols.
3. Results and Discussions
Design and Implementation System Design
In this design, several related components in terms of functionality
have been grouped to form sub-systems which combine to make up
the whole system. Breaking the system down to components and
sub- systems informs the logical design of the class attendance
system. The flow diagram of Figure 5 depicts the systems operation.
Volume1 Issues 11 from Nov- 2020
INTERNATIONAL REFEREED JOURNAL OF ENGINEERING SCIENCE ANDTECHNOLOGY www.irjest.com
IRJEST @ www.irjest.com
Fig.5 The flowchart to depict system operation
The figure 5 is employed at different stages of face
recognition systems.
Fig.6. Overview of the system operation design
According to figure 6, the student needs to be in front of a camera
at a minimum distance of 60cm.The system will detect the image of
the student according to PCA 13 converts it into a gray scale and
stores it in an xml file. When the student reappears before the
camera, faces are recognized by comparing the Eigen faces of
current and stored images. The names of the detected faces are
then stored in Microsoft Access Database.
Arduino Architecture
Arduino's processor essentially utilizes the Harvard design where
the program code and program information have separate
memory. It comprises of two recollections Program memory and
the information memory. The code is stored in the flash program
memory, whereas the data is stored in the data memory. The
Atmega328 has 32 KB of flash memory for storing code (of which
0.5 KB is used for the boot loader), 2 KB of SRAM and 1 KB of
EEPROM and operates with a clock speed of 16MHz. Figure 7 show
a typical architecture of an Arduino.
Fig.7 Typical Arduino Architecture
Volume1 Issues 11 from Nov- 2020
INTERNATIONAL REFEREED JOURNAL OF ENGINEERING SCIENCE ANDTECHNOLOGY www.irjest.com
IRJEST @ www.irjest.com
Arduino Programming-Arduino Software
The main bit of leeway with Arduino is the projects can be
straightforwardly stacked to the gadget without requiring any
equipment developer to consume the program. The 0.5KB of
Boot loader allows the program to be burned into the circuit.
The Arduino Software (IDE) allows writing programs and
uploading it to board. The Arduino Software consists of two
options: online (Arduino Web Editor) and the other offline IDE
(the latest version of the desktop IDE).These allow saving
sketches in the cloud and make it available from any device
backup rather to install updates or community generated
libraries.
The five steps to program an Arduino are:
Step1: To write sketches. Sketches are programs written in
Arduino which consists of declaration of variables,
initialization and control code.
Step 2: The sketch is saved within extension. Any tasks like
confirming, opening a sketch, sparing a sketch should be
possible utilizing the catches on the toolbar or utilizing the
apparatus menu
Step 3: The sketch should be stored in the sketchbook
directory.
Step 4: Chose the proper board from the tools menu and the
serial port numbers.
Step 5: Click on the upload button or chose upload from the
tools menu. The sample code is then uploaded by the boot
loader onto the microcontroller.
LCD Interfacing with the Arduino Module – Robot Design
Figure 8 show the liquid crystal display with the Arduino
module. The RS pin of the LCD in the circuit is connected to the
pin 12 of the Arduino. The LCD of R/W pin is associated with the
ground..
The pin 11 of the Arduino is connected to the enable signal pin
of LCD module. There are four input lines from DB4 to DB7 of
the LCD in the circuit. The LCD module &Arduino module are
interfaced with the 4-bit mode using fewer connection cables
in this project.
Fig.8 Schematic diagram of LCD interfacing with
Arduino
The computerized input lines (DB4-DB7) are interfaced with the
Arduino pins from 5-2. A 10K potentiometer is used to adjust the
contrast of the display. The current through the back LED light is
from the 560-ohm resistor. The outer force jack is given by the board
to the Arduino. Utilizing the PC through the USB port the Arduino
can control some parts of the circuit can require the +5V power
supply it is taken from the 5V source on the Arduino board.
Volume1 Issues 11 from Nov- 2020
INTERNATIONAL REFEREED JOURNAL OF ENGINEERING SCIENCE ANDTECHNOLOGY www.irjest.com
IRJEST @ www.irjest.com
Fig.9 LCD –Arduino Interfacing in a breadboard
Connection
• Do you get a similar incentive from the advanced port in
both 3.3V and 5V?
Testing the SQL Server
The testing is done to check whether the server is turned on/off
before starting the SQL database separately or in visual studio.
Step 1
Press the windows key + R keys to open the ‘run’ popup menu.
Step2
Press win + R (windows key + R key) in the popup menu. Type
services msc on the run menu and press enter.
Step 3
Scroll down the screen and check until the SQL server created is
running or not. If it is not running click on the server and press
start button on the left top corner.
Start-up Data base in Visual studio Step 1
Testing
Software Startup
To launch the Arduino Application, Double-click the
Arduino application in the folder from where it is
extracted.
Open example code select board upload
program Select serial port
Read data
Testing the Arduino Uno Board
Connect one end of the wire to A0 port
Associate the opposite finish to GND port
Analog0 in the Serial Monitor should now peruse 0.0
volts Remove the wire from GND and connect it to 5V
Analog0 should now read approximately 5.0 volts
Eliminate the wire from GND and associate it to 5V
Analog0 should now peruse roughly 3.3 volts
Rehash a similar technique with A1, D2 and D3
Open the VS and click on the tools menu on the menu bar and
select connect to database.
Step 2
A new popup window will appear. Type the created SQL server
name and the database name and click on the ok button or press
enter key.
Step 3
The database and the server is connected with the VS. The red
color sign database connection indicates that the server is not
connected. Press on the refresh button to refresh the connection
and check for a bluish green color sign indication for proper server
connection.
Volume1 Issues 11 from Nov- 2020
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Output
Fig.11 Login page
Fig.12 Login as Admin
Fig.13 Image collector
Fig.14 Face Extractor
Fig.15 Face Adder
Fig.16 Face Recognition Using Image
Volume1 Issues 11 from Nov- 2020
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IRJEST @ www.irjest.com
Fig.17 Face Recognition Using Camera
Fig.18 Persons details
Conclusion:
Exploratory investigation and study show that the
progressive security structures are viable fit as a fiddle
recognizable proof for physiological qualities. The facial
expression based face recognition system is made efficient
with genetic algorithm invariants of the facial surface
resulting to a recognition rate of 95.4%. The illustration of the
model given in this research work is to build expressional
representations using the concept of hierarchy based
embedding approach. The facial portrayal model is conveyed
in PC for biometric confirmation measure. The effect of the
installing space decision on the measurement (bending)
presumes that spaces with round calculation are more
positive for portrayal of facial surfaces. This exploration work
guarantees another heading of examination in the field of
asymmetric biometric cryptosystems which is highly
desirable in order to get rid of passwords and smart
References
1) R. Jafri, H. R. Arabnia, “A Survey of Face Recognition
Techniques”, Journal of Information Processing Systems,
Vol.5, No.2, June 2009.
2) C. A. Hansen, “Face Recognition”, Institute for Computer
Science University of Tromso, Norway.
3) M. D. Kelly. Visual identification of people by computer.
PhD thesis, Stanford University, Stanford, CA, USA, 1971.
4) T. Kanade. Computer Recognition of Human Faces, 47,
1977.
5) W. Zhao, R. Chellappa, P. J. Phillips & A. Rosenfeld, “Face
6) recognitions literature
7) survey”, ACM Computing Surveys, Vol. 35, No. 4,
December 2003, pp. 399–458.
8) C. Gonzalez, R. E. Woods, S. liddins, "Digital Image
processing Using MATLAB".
9) S. Suhas, A. Kurhe, Dr.P. Khanale, “Face Recognition
Using Principal Component Analysis and Linear
Discriminant Analysis on Holistic Approach in Facial
Images
10) Database”, IOSR Journal of Engineering e-ISSN: 2250-
3021, p-ISSN: 2278-8719, Vol. 2, Issue 12 (Dec. 2012),
11) ||V4|| PP 15-23
12) M. A. Turk and A. P. Pentland, "Face Recognition Using
Eigenfaces", 1991.
13) S. Asadi, Dr. D. V. Subba R. V. Saikrishna, "A Comparative
study of Face Recognition with PCA and Cross-
Correlation Technique", IJCA (0975-8887), Volume 10-
No.8, November 2010.
14) E. A. Abusham, A. T. B. Jin, W. E. Kiong, "Face
Recognition Based on Nonlinear Feature Approach",
American Journal of Applied Sciences, 2008.
15) Nigam, P. Gupta, "A New Distance Measure for Face
Recognition System", 2009 Fifth International Conference
on Image and Graphics