CFP last date
20 January 2025
Reseach Article

Human Face Detection by Using Skin Color Segmentation, Face Features and Regions Properties

by Devendra Singh Raghuvanshi, Dheeraj Agrawal
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 38 - Number 9
Year of Publication: 2012
Authors: Devendra Singh Raghuvanshi, Dheeraj Agrawal
10.5120/4715-6881

Devendra Singh Raghuvanshi, Dheeraj Agrawal . Human Face Detection by Using Skin Color Segmentation, Face Features and Regions Properties. International Journal of Computer Applications. 38, 9 ( January 2012), 14-17. DOI=10.5120/4715-6881

@article{ 10.5120/4715-6881,
author = { Devendra Singh Raghuvanshi, Dheeraj Agrawal },
title = { Human Face Detection by Using Skin Color Segmentation, Face Features and Regions Properties },
journal = { International Journal of Computer Applications },
issue_date = { January 2012 },
volume = { 38 },
number = { 9 },
month = { January },
year = { 2012 },
issn = { 0975-8887 },
pages = { 14-17 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume38/number9/4715-6881/ },
doi = { 10.5120/4715-6881 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:24:57.519777+05:30
%A Devendra Singh Raghuvanshi
%A Dheeraj Agrawal
%T Human Face Detection by Using Skin Color Segmentation, Face Features and Regions Properties
%J International Journal of Computer Applications
%@ 0975-8887
%V 38
%N 9
%P 14-17
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The goal of face detection is to lo­cate all regions that contain a face. This pa­per has a simple face detection procedure which has two major steps, first to segment skin region from an image, and second, to decide these regions contain human face or not. Our procedure is based on skin color segmentation and human face features (knowledge-based approach). In this paper, we used RGB, YCbCr, CEILAB (L*a*b) and HSV color models for skin color segmentation. These color models with thresholds, help to remove non skin like pixels from an image. We tested each skin region, that skin region is actually represents a human face or not, by using human face features based on knowledge of geometrical properties of human face. The experiment result shows that, the algorithm gives hopeful results. At last, we concluded this paper and proposed future work.

References
  1. Ming-Hsuan Yang, member, IEEE, David J. Kriegman, Senior Member, IEEE, and Narendra Ahuja, Fellow, IEEE. “Detecting Faces in Images: A Survey”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. no. 1, January 2002.
  2. J. Liu and Y. H. Yang, “Multiresolution Color Image Segmentation”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 16, No. 7, pp. 689-700, 1994.
  3. . Sanjay Kr. Singh1, D. S. Chauhan2, Aayank Vatsa, Richa Singh “A Robust Skin Color Based Face Detection Algorithm”, Tamkang Journal of Science and Engineering, Vol. 6, No. 4, pp. 227-234, 2003.
  4. R. Vijayanandh, Dr. G. Balakrishnan, “Human Face Detection Using Color Spaces and Region Property Measures”, 2010 11th Int. Conf. Control, Automation, Robotics and Vision Singapore, December 2010.
  5. Murad Al Haj, Ariel Amato, Xavier Roca, and Jordi Gonzalez, “Finding Faces in Color Images through Primitive Shape Features”, Computer Vision Center, Department d’Inform atica, Universitat Autonoma de Barcelona, 08193 Bellaterra, Barcelona, Spain, Institut de Robotica i Informatica Industrial (UPC-CSIC), Barcelona, Spain.
  6. Waqar Mohsin Noman Ahmed khattak, “Face Detection Project”, EE368 Digital Image Processing, Spring 02, 03, Department of Electrical Engineering Stanford University, 2002-2003.
  7. C . N. Ravi Kumar, Bindhu A, “ An Efficient Skin Illumination Compensation Model for Efficient Face Detection”, 2010.
  8. Yihu Yi, Daokui Qu, Fang Xu, ” Face Detection Method Based on Skin Color Segmentation and Facial Component Localization”, 2nd International Asia Conference on Informatics in Control, Automation and Robotics, 20 I0.
Index Terms

Computer Science
Information Sciences

Keywords

Color Segmentation Face Features