Segmentation-based illumination normalization for face detection
- Resource Type
- Conference
- Authors
- Yao, Min; Aoki, Kota; Nagahashi, Hiroshi
- Source
- 2013 IEEE 6th International Workshop on Computational Intelligence and Applications (IWCIA) Computational Intelligence & Applications (IWCIA), 2013 IEEE Sixth International Workshop on. :95-100 Jul, 2013
- Subject
- Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Lighting
Face
Detectors
Face detection
Image segmentation
Histograms
Learning systems
face detection
Haar-like face detector
illumination normalization
Otsu method
segmentation-based
- Language
- ISSN
- 1883-3977
Face detection is an important research topic in the field of computer vision. Illumination problem is one of the most important aspects impeding the effectiveness of face detection. The well known Haar-like face detector developed by Viola and Jones is also largely weakened under adverse lighting conditions such as backlighting or uneven lighting. In this paper, a novel segmentation-based illumination normalization method is presented for the purpose of compensating non-uniform illuminations and increasing the robustness of Haar-like face detector. First Otsu method is employed to segment the input image. Then the proposed illumination normalization method called Half Histogram Truncation and Stretching (HHTS) is applied to locally attenuate the illumination and enhance the visibility of local patterns (facial structures). Finally Haar-like face detector is executed to locate faces. Experimental results show that it can remove non-uniform illuminations efficiently and significantly increase the performance of the original Haar-like face detector.