Human face detection using skin color tone /

Human face recognition systems have gained a considerable attention during last decade due to its vast applications in the field of computer and advantages over previous biometric methods. There are many applications with respect to security, sensitivity and secrecy. Human face detection is the most...

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Bibliographic Details
Main Author: Mohialdeen, Hewa Majeed
Format: Thesis
Language:English
Published: Kuala Lumpur : Kulliyyah of Information and Communication Technology, International Islamic University Malaysia, 2013
Subjects:
Online Access:http://studentrepo.iium.edu.my/handle/123456789/5405
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040 |a UIAM  |b eng 
041 |a eng 
043 |a a-my--- 
050 0 0 |a TA1650 
100 1 |a Mohialdeen, Hewa Majeed  
245 1 |a Human face detection using skin color tone /  |c by Hewa Majeed Mohialdeen 
260 |a Kuala Lumpur :  |b Kulliyyah of Information and Communication Technology, International Islamic University Malaysia,   |c 2013 
300 |a xii, 70 leaves :  |b ill. ;  |c 30cm. 
502 |a Thesis (MIT)--International Islamic University Malaysia, 2013. 
504 |a Includes bibliographical references (leaves 60-64). 
520 |a Human face recognition systems have gained a considerable attention during last decade due to its vast applications in the field of computer and advantages over previous biometric methods. There are many applications with respect to security, sensitivity and secrecy. Human face detection is the most important and first step of recognition system. This dissertation introduces a new approach to face detection systems using the skin color of a subject. This system can detect a face regardless of the background of the picture, which is an important phase for face identification. The images used in this system are color images which give additional information about the image than the gray images provide. In human face detection, the Two respective classes are the "face area" and the "non-face area". This new approach to face detection is based on color tone values specially defined for skin area detection within the image frame. The proposed system first resizes the image, and then separates it into its component R, G, and B bands. These bands are transformed into another color space which is YCbCr space and then into YC'bC'r space (the skin color tone). The morphological process is implemented on the presented image to make it more accurate. At last, the projection face area is taken by this system to determine the face area. Experimental results show that the proposed algorithm is good enough to localize a human face in an image with an accuracy of 92.69%. 
596 |a 1 
655 7 |a Theses, IIUM local 
690 |a Dissertations, Academic  |x Department of Information Systems  |z IIUM 
710 2 |a International Islamic University Malaysia.  |b Department of Information Systems 
856 4 |u http://studentrepo.iium.edu.my/handle/123456789/5405 
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