Contrast compensation for back-lit and front-lit color face images via fuzzy logic classification and image illumination analysis

Chun Ming Tsai, Zong M.U. Yeh, Yuan Fang Wang

研究成果: 書貢獻/報告類型會議論文篇章

摘要

Conventional contrast enhancement methods have two shortcomings. First, most of them do not produce satisfactory enhancement results for face images with back-lit or front-lit. Second, most of them need transformation functions and parameters which are specified manually. Thus, this paper proposes an automatic and parameter-free contrast compensation algorithm for color face images. This method includes: RGB color space is transformed to YIQ color space. Fuzzy logic is used to classify the color images into back-lit, normal-lit, and front-lit categories. Image illumination analysis is used to analyze the image distribution. The input image is compensated by piecewise linear based compensation method. Finally, the compensation image is transformed back to RGB color space. This novel compensation method is automatic and parameter-free. Our experiments included back-lit and front-lit images. Experiment results show that the performance of the proposed method is better than other available methods in visual perception measurements.

原文英語
主出版物標題Proceedings of the 7th International Conference on Machine Learning and Cybernetics, ICMLC
頁面3563-3568
頁數6
DOIs
出版狀態已發佈 - 2008 十二月 29
事件7th International Conference on Machine Learning and Cybernetics, ICMLC - Kunming, 中国
持續時間: 2008 七月 122008 七月 15

出版系列

名字Proceedings of the 7th International Conference on Machine Learning and Cybernetics, ICMLC
6

其他

其他7th International Conference on Machine Learning and Cybernetics, ICMLC
國家/地區中国
城市Kunming
期間2008/07/122008/07/15

ASJC Scopus subject areas

  • 人工智慧
  • 人機介面
  • 控制與系統工程

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