Skin colour based face detection

Son Lam Phung, D. Chai, A. Bouzerdoum

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Citations (Scopus)

Abstract

This paper describes a new approach to face detection. A colour input image is first processed using neural networks to detect skin regions in the image. Each neural network separates skin and non-skin pixels on the basis of chrominance information. The skin-colour classifier employs the committee machine technique, which improves skin colour detection by combining the classification results of a set of multilayer perceptrons (MLPs). The skin colour classifier achieves a classification rate of 84% compared to 81% for the best individual MLP classifier. The output of the committee machine is processed by a 2D smoothing filter before being converted into a binary map using a threshold. Finally, several post-processing techniques based on shape and luminance features are proposed for rejecting non-facial regions.

Original languageEnglish
Title of host publicationANZIIS 2001 - Proceedings of the 7th Australian and New Zealand Intelligent Information Systems Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages171-176
Number of pages6
ISBN (Electronic)1740520610, 9781740520614
DOIs
Publication statusPublished - 2001
Externally publishedYes
Event7th Australian and New Zealand Intelligent Information Systems Conference, ANZIIS 2001 - Perth, Australia
Duration: 18 Nov 200121 Nov 2001

Publication series

NameANZIIS 2001 - Proceedings of the 7th Australian and New Zealand Intelligent Information Systems Conference

Conference

Conference7th Australian and New Zealand Intelligent Information Systems Conference, ANZIIS 2001
Country/TerritoryAustralia
CityPerth
Period18/11/0121/11/01

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