Automated Face Detection Using Skin Color Segmentation and Viola-Jones Algorithm

Viola-Jones algorithm can be categorized as one of an established and effective method (feature-based approach) for detecting face. It consists of three main processes which are Haar features, Adaboost and Cascading. These processes involved scanning the patterns of human face through all the pixels...

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Main Authors: Ahmad Fakhri, Ab. Nasir, Ahmad Shahrizan, Abdul Ghani, Muhammad Aizzat, Zakaria, Anwar, P. P. Abdul Majeed, Ahmad Najmuddin, Ibrahim
Format: Article
Language:English
Published: Penerbit UMP 2019
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/26527/
http://umpir.ump.edu.my/id/eprint/26527/1/Automated%20Face%20Detection%20Using%20Skin%20Colour.pdf
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author Ahmad Fakhri, Ab. Nasir
Ahmad Shahrizan, Abdul Ghani
Muhammad Aizzat, Zakaria
Anwar, P. P. Abdul Majeed
Ahmad Najmuddin, Ibrahim
author_facet Ahmad Fakhri, Ab. Nasir
Ahmad Shahrizan, Abdul Ghani
Muhammad Aizzat, Zakaria
Anwar, P. P. Abdul Majeed
Ahmad Najmuddin, Ibrahim
author_sort Ahmad Fakhri, Ab. Nasir
building UMP Institutional Repository
collection Online Access
description Viola-Jones algorithm can be categorized as one of an established and effective method (feature-based approach) for detecting face. It consists of three main processes which are Haar features, Adaboost and Cascading. These processes involved scanning the patterns of human face through all the pixels in the image. In the empirical experiment by using this algorithm, some region in the image which is supposed to be non-face region is detected as face due to the similarity of human face features. In addition, this approach only search for pattern (feature) but leaving the color information. Therefore, this paper proposes hybridization of skin color segmentation in prior to Viola-Jones algorithm. Several images with different kinds of environment (different light conditions, different face orientation) and various people ethnics (Malay, Chinese, Indian, etc.) are tested using the improved algorithm and the original Viola-Jones algorithm as well. In average, experimental results reveal the combination of YCbCr color and Viola-Jones algorithm is the best model (average accuracy is ~88%) to detect human face in various conditions. Other color model such as HSV and benchmarked algorithm are having slightly low detection rates due to some false face detection. Despite of this, this research also found that both YCbCr and HSV color model are having some limitation when dealing with darker face and lightning condition since the skin color become slightly out of range from normal skin color distribution.
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institution Universiti Malaysia Pahang
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spelling ump-265272019-11-21T05:53:58Z http://umpir.ump.edu.my/id/eprint/26527/ Automated Face Detection Using Skin Color Segmentation and Viola-Jones Algorithm Ahmad Fakhri, Ab. Nasir Ahmad Shahrizan, Abdul Ghani Muhammad Aizzat, Zakaria Anwar, P. P. Abdul Majeed Ahmad Najmuddin, Ibrahim TJ Mechanical engineering and machinery Viola-Jones algorithm can be categorized as one of an established and effective method (feature-based approach) for detecting face. It consists of three main processes which are Haar features, Adaboost and Cascading. These processes involved scanning the patterns of human face through all the pixels in the image. In the empirical experiment by using this algorithm, some region in the image which is supposed to be non-face region is detected as face due to the similarity of human face features. In addition, this approach only search for pattern (feature) but leaving the color information. Therefore, this paper proposes hybridization of skin color segmentation in prior to Viola-Jones algorithm. Several images with different kinds of environment (different light conditions, different face orientation) and various people ethnics (Malay, Chinese, Indian, etc.) are tested using the improved algorithm and the original Viola-Jones algorithm as well. In average, experimental results reveal the combination of YCbCr color and Viola-Jones algorithm is the best model (average accuracy is ~88%) to detect human face in various conditions. Other color model such as HSV and benchmarked algorithm are having slightly low detection rates due to some false face detection. Despite of this, this research also found that both YCbCr and HSV color model are having some limitation when dealing with darker face and lightning condition since the skin color become slightly out of range from normal skin color distribution. Penerbit UMP 2019 Article PeerReviewed pdf en cc_by_nc_4 http://umpir.ump.edu.my/id/eprint/26527/1/Automated%20Face%20Detection%20Using%20Skin%20Colour.pdf Ahmad Fakhri, Ab. Nasir and Ahmad Shahrizan, Abdul Ghani and Muhammad Aizzat, Zakaria and Anwar, P. P. Abdul Majeed and Ahmad Najmuddin, Ibrahim (2019) Automated Face Detection Using Skin Color Segmentation and Viola-Jones Algorithm. Mekatronika - Journal of Intelligent Manufacturing & Mechatronics, 1 (1). pp. 58-63. ISSN 2637-0883. (Published) http://journal.ump.edu.my/mekatronika/article/view/375 https://doi.org/10.15282/mekatronika .v1i1.375
spellingShingle TJ Mechanical engineering and machinery
Ahmad Fakhri, Ab. Nasir
Ahmad Shahrizan, Abdul Ghani
Muhammad Aizzat, Zakaria
Anwar, P. P. Abdul Majeed
Ahmad Najmuddin, Ibrahim
Automated Face Detection Using Skin Color Segmentation and Viola-Jones Algorithm
title Automated Face Detection Using Skin Color Segmentation and Viola-Jones Algorithm
title_full Automated Face Detection Using Skin Color Segmentation and Viola-Jones Algorithm
title_fullStr Automated Face Detection Using Skin Color Segmentation and Viola-Jones Algorithm
title_full_unstemmed Automated Face Detection Using Skin Color Segmentation and Viola-Jones Algorithm
title_short Automated Face Detection Using Skin Color Segmentation and Viola-Jones Algorithm
title_sort automated face detection using skin color segmentation and viola-jones algorithm
topic TJ Mechanical engineering and machinery
url http://umpir.ump.edu.my/id/eprint/26527/
http://umpir.ump.edu.my/id/eprint/26527/
http://umpir.ump.edu.my/id/eprint/26527/
http://umpir.ump.edu.my/id/eprint/26527/1/Automated%20Face%20Detection%20Using%20Skin%20Colour.pdf