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Proceedings Paper

Shadow detection and removal based on the saliency map
Author(s): Zhiwen Fang; Zhiguo Cao; Chunhua Deng; Ruicheng Yan; Yueming Qin
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Paper Abstract

The detection of shadow is the first step to reduce the imaging effect that is caused by the interactions of the light source with surfaces, and then shadow removal can recover the vein information from the dark region. In this paper, we have presented a new method to detect the shadow in a single nature image with the saliency map and to remove the shadow. Firstly, RGB image is transferred to 2D module in order to improve the blue component. Secondly, saliency map of blue component is extracted via graph-based manifold ranking. Then the edge of the shadow can be detected in order to recover the transitional region between the shadow and non-shadow region. Finally, shadow is compensated by enhancing the image in RGB space. Experimental results show the effectiveness of the proposed method.

Paper Details

Date Published: 27 October 2013
PDF: 6 pages
Proc. SPIE 8919, MIPPR 2013: Pattern Recognition and Computer Vision, 89190I (27 October 2013); doi: 10.1117/12.2031134
Show Author Affiliations
Zhiwen Fang, Huazhong Univ. of Science and Technology (China)
Hunan Univ. of Humanities, Science and Technology (China)
Zhiguo Cao, Huazhong Univ. of Science and Technology (China)
Chunhua Deng, Huazhong Univ. of Science and Technology (China)
Ruicheng Yan, Huazhong Univ. of Science and Technology (China)
Yueming Qin, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 8919:
MIPPR 2013: Pattern Recognition and Computer Vision
Zhiguo Cao, Editor(s)

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