Local contrast enhancement for human face recognition in poor lighting conditions

Wen Chung Kao, Ming Chai Hsu

研究成果: 雜誌貢獻Conference article

2 引文 (Scopus)

摘要

Recognizing human faces in various lighting conditions is quite difficult for a surveillance system. The problem becomes more difficult if face images are taken in extremely high dynamic range scenes. Most of automatic face recognition systems assume the images are taken under well controlled illumination. The face segmentation as well as recognition problem is much simpler under such a constrained condition. However, controlling illumination is not feasible while the surveillance system is installed on locations at will. Without compensating for the effect of uneven illuminants, it is impossible to get a satisfactory recognition result. In this paper, we propose an integrated system that first compensates illuminant effect by local contrast enhancement. Then the enhanced images are fed into a robust face recognition engine which adaptively selects important features and performs classification by support vector machines (SVMs). The experimental result shows that the proposed recognition system is better than recently published literatures with two popular human face image databases.

原文英語
文章編號4811288
頁(從 - 到)277-282
頁數6
期刊Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
DOIs
出版狀態已發佈 - 2008 十二月 1
事件2008 IEEE International Conference on Systems, Man and Cybernetics, SMC 2008 - Singapore, 新加坡
持續時間: 2008 十月 122008 十月 15

指紋

Face recognition
Lighting
Support vector machines
Engines

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Human-Computer Interaction

引用此文

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