Framework for feature selection for cast shadow removal

Guilin Zhang; Ying Chu; Song Tian; Yufei Zha; Gengming Zhu

doi:10.1117/12.748631

15 November 2007 Framework for feature selection for cast shadow removal

Guilin Zhang, Ying Chu, Song Tian, Yufei Zha, Gengming Zhu

Proceedings Volume 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition; 678606 (2007) https://doi.org/10.1117/12.748631
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

Cast shadow cause serious problem in the extracting of moving objects because shadow pixels are liable to be misclassified as foreground. Many methods of cast shadow removal have been proposed and many features are selected in these methods. But since, moving object (MO) and cast shadow are classified by a single linear classifier. As it is known, each feature has its strength and weakness and is particularly applicable for handling a certain type of variation. In this paper, a novel framework for feature selection for cast shadow removal based on AdaBoost is proposed. Experiments are conducted on many scenes and the results prove the validation of the proposed method.

Citation Download Citation

Guilin Zhang, Ying Chu, Song Tian, Yufei Zha, and Gengming Zhu "Framework for feature selection for cast shadow removal", Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 678606 (15 November 2007); https://doi.org/10.1117/12.748631

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KEYWORDS

Bromine

Feature selection

RGB color model

Light sources

Feature extraction

Reflectivity

Communication engineering

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