Face Detection in Color Images.

Date of Submission

December 2004

Date of Award

Winter 12-12-2005

Institute Name (Publisher)

Indian Statistical Institute

Document Type

Master's Dissertation

Degree Name

Master of Technology

Subject Name

Computer Science


Machine Intelligence Unit (MIU-Kolkata)


Murthy, C. A. (MIU-Kolkata; ISI)

Abstract (Summary of the Work)

Face recognition has received substantial attention from researchers in biometrics, computer vision, patterm recognition, and cognitive psychology communities because of the increased attention being devoted to security, man- machine communication, content-based image retrieval, and image/video coding. Three major tasks involved in face recognition systems are: (i) face detection, (i) face modeling, and (iii) face matching. So Face Detection is an essential step in face recognition.We have developed a face detection algorithm for color images that can detect faces with different sizes and various poses from both indoor and outdoor scenes. The goal of this dissertation is to detect all regions that may contain faces while maintaining a low false positive output rate. We first develop a skin color detector based on color analysis and the fuzzy set theory, whose performance is much better than the existing skin region detectors. We also develop a hair color detector, which makes possible the use of the hair part as well as the skin part in face detection. We design multiple head-shape models to cope with the variation of the head pose. We propose a fuzzy set theory based pattern-matching technique, and use it to detect face candidates by finding out patterns similar to the prebuilt head-shape models from the extracted skin and hair regions.The utility of the proposed method is determination of faces at a faster rate, and accurately. The multiple head pose models allow it to detect faces of various poses. This method is not affected by iocal changes in a face and hence the method is not sensitive to change in facial expression and the results are good.


ProQuest Collection ID: http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:28843113

Control Number


Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.



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