Face detection based on skin color in image by neural networks

Aamer S.S. Mohamed, Ying Weng, Stan S. Ipson, Jianmin Jiang

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

15 Citations (Scopus)

Abstract

Face detection is one of the challenging problems in the image processing . A novel face detection system is presented in this paper. The approach relies on skin based color , while features extracted from two dimentional Discreate cosine transfer (DCT) and neural networks . which can be used to detect faces by using skin color from DCT coefficient of Cb and Cr feature vectors. This system contains the skin color which is the main feature of faces for detection ,and then the skin face candidate is examined by using the neural networks, which learns from the feature of faces to classify whether the original image includes a face or not. The processing stage is based on normalization and Discreate Cosin transfer (DCT). Finally the classification based on neural networks approch. The expriments results on upright frontal color face images from the internt show an a exellent detection rate.

Original languageEnglish
Title of host publication2007 International Conference on Intelligent and Advanced Systems, ICIAS 2007
Pages779-783
Number of pages5
DOIs
Publication statusPublished - 2007
Externally publishedYes
Event2007 International Conference on Intelligent and Advanced Systems, ICIAS 2007 - Kuala Lumpur, Malaysia
Duration: 25 Nov 200728 Nov 2007

Publication series

Name2007 International Conference on Intelligent and Advanced Systems, ICIAS 2007

Conference

Conference2007 International Conference on Intelligent and Advanced Systems, ICIAS 2007
Country/TerritoryMalaysia
CityKuala Lumpur
Period25/11/0728/11/07

Keywords

  • Compressed domain
  • Face detection
  • Neural networks
  • Skin color segmentation

ASJC Scopus subject areas

  • Artificial Intelligence
  • Control and Systems Engineering

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