THDC Institute of Hydropower Engineering and Technology Tehri Gharwal, UttarakhandIndia

Project Report on

Face Recognition System Using Image Processing in Matlab

by

Kamlesh Singh Piyush Rawat Anish Kaushik Kumar(Electronics and Communication Engineering 3rd Year)

Under Guidance of Mr. Ashish JoshiAssistant ProfessorDepartment Of Computer ScienceTHDC Institute of Hydropower Engineering and TechnologyTehri Gharwal, UttarakhandIndia.

Table of Content

1. LIST OF FIGURE i

2. ACKNOWLEDGEMENT1

3. SOFTWARE REQUIREMENT 2

4. PROJECT SPECIFICATION3

4.1. Objective 4.2. Project overview

5. CODE STRUCTURE5

6. RESULT7

7. REFERENCE & BIBLIOGRAPHY 8

LIST OF FIGURE

Figure 2.1Matlab R2012b GUI.

Figure 4.1Code written in command window of Matlab

Figure 6.1Face detected as a result

ACKNOWLEDGEMENT

Wewould like to express our special thanks of gratitude to our teacher Mr. Ashish Joshi, Assistant Professor, THDC IHET who gave us the golden opportunity to do this wonderful project on the topic Face Recognition System Using Image Processing in Matlab, which also helped us in doing a lot of Research and we came to know about so many new things we are really thankful to him.

Kamlesh Singh Piyush Rawat Anish Kaushik Kumar

SOFTWARE REQUIREMENT :MATLAB

MATLABis a high-level language and interactive environment for numerical computation, visualization, and programming. Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as C/C++ or Java.

You can use MATLAB for a range of applications, including signal processing and communications, image and video processing, control systems, test and measurement, computational finance, and computational biology. More than a million engineers and scientists in industry and academia use MATLAB, the language of technical computing.

Fig. 3.1 Matlab R2012b GUI.

PROJECT SPECIFICATION

OBJECTIVE

Face recognition is the process of identifying one or more people in images or videos. Algorithms for face recognition typically extract facial features and compare them to a database to find the best match. The objective of Face recognition is important part of many biometric, security, and surveillance systems, as well as image and video indexing systems.

.PROJECT OVERVIEW

In our project we studied the basics of Matlab and the image processing toolbox that took almost 20 days.

To find out information about my topic, we first started with the matlab basics and then the image processing toolbox in it. After that we focused our main project i.e. how it works, did a lot of research on it from the previously did project o it and Mathworks, a privately held, multi-national corporation that specializes in mathematical computing software including MATLAB and Simulink.

The following topics we came to know-

Image ProcessingImage processingis any form ofsignal processingfor which the input is an image, such as aphotographorvideo frame; theoutputof image processing may be either an image or a set of characteristics orparametersrelated to the image. Most image-processing techniques involve treating the image as atwo-dimensionalsignaland applying standard signal-processing techniques to it.An image defined in the real world is considered to be a function of two real variables, for example, a(x,y) with a as the amplitude (e.g. brightness) of the image at the real coordinate position (x,y).

Image Processing Toolbox:

Image Processing Toolbox provides a comprehensive set of reference-standard algorithms, functions, andapps for image processing, analysis, visualization, and algorithm development. You can performimage enhancement, image deblurring, feature detection, noise reduction,image segmentation, geometric transformations, and image registration. Many toolbox functions are multithreaded to take advantage of multicore and multiprocessor computers.Image Processing Toolbox supports a diverse set of image types, including high dynamic range, gigapixel resolution, embedded ICC profile, and tomographic.Visualization functionslet you explore an image, examine a region of pixels, adjust the contrast, create contours or histograms, and manipulate regions of interest (ROIs). Withtoolbox algorithmsyou can restore degraded images, detect and measure features,analyze shapesand textures, and adjust color balance.

CODE STRUCTURE

faceDetector = vision.CascadeObjectDetector();videoFileReader = vision.VideoFileReader('visionface.avi');videoFrame = step(videoFileReader);bbox = step(faceDetector, videoFrame);videoOut = insertObjectAnnotation(videoFrame,'rectangle',bbox,'Face');figure, imshow(videoOut), title('Detected face');[hueChannel,~,~] = rgb2hsv(videoFrame);figure, imshow(hueChannel), title('Hue channel data');rectangle('Position',bbox(1,:),'LineWidth',2,'EdgeColor',[1 1 0])noseDetector = vision.CascadeObjectDetector('Nose');faceImage = imcrop(videoFrame,bbox(1,:));noseBBox = step(noseDetector,faceImage);noseBBox(1,1:2) = noseBBox(1,1:2) + bbox(1,1:2);tracker = vision.HistogramBasedTracker;initializeObject(tracker, hueChannel, noseBBox(1,:));videoInfo = info(videoFileReader);videoPlayer = vision.VideoPlayer('Position',[300 300 videoInfo.VideoSize+30]);while ~isDone(videoFileReader) videoFrame = step(videoFileReader);[hueChannel,~,~] = rgb2hsv(videoFrame);bbox = step(tracker, hueChannel);videoOut = insertObjectAnnotation(videoFrame,'rectangle',bbox,'Face');step(videoPlayer, videoOut);endrelease(videoFileReader);release(videoPlayer);

(THIS CODE IS SHOWN IN FIG.4.1)

Fig.5.1 code written in command window of matlab

RESULT

This is quite evident from the figure.6.1 that image processing using MATLAB has been done successfully.

Fig.6.1 Face detected as a result.

REFERENCE & BIBLIOGRAPHY

1. MATLAB Image Processing By Bruce Tannenbaum IEEE Boston Meeting, Dec 3, 20122. A MATLAB based Face Recognition System using Image Processing and Neural Networks by Jawad Nagi, Syed Khaleel Ahmed, Farrukh Nagi, Universiti Tenaga Nasional, Malaysia.3. Mathwork : www.mathwork.com 4. Wikipedia : en.wikipedia.org

CERTIFICATE

TO WHOMEVER IT MAY CONCERN

This is to certify that following students of THDC-IHET, Tehri have successfully completed and submitted their project in FACE RECOGNITION SYSTEM USING IMAGE PROCESSING IN MATLAB.

PIYUSH RAWAT (ECE 3rd year) KAMLESH SINGH (ECE 3rd year)

ANISH (ECE 3rd year) KAUSHIK KUMAR (ECE 3rd year)

Mr. ASHISH JOSHIAssistant ProfessorDepartment Of Computer scienceTHDC-IHET,Tehri.