WLD : a robust local image descriptor

Inspired by Weber's Law, this paper proposes a simple, yet very powerful and robust local descriptor, called the Weber Local Descriptor (WLD). It is based on the fact that human perception of a pattern depends not only on the change of a stimulus (such as sound, lighting) but also on the origin...

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Veröffentlicht in:IEEE transactions on pattern analysis and machine intelligence. - 1979. - 32(2010), 9 vom: 15. Sept., Seite 1705-20
1. Verfasser: Chen, Jie (VerfasserIn)
Weitere Verfasser: Shan, Shiguang, He, Chu, Zhao, Guoying, Pietikäinen, Matti, Chen, Xilin, Gao, Wen
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2010
Zugriff auf das übergeordnete Werk:IEEE transactions on pattern analysis and machine intelligence
Schlagworte:Journal Article Research Support, Non-U.S. Gov't
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520 |a Inspired by Weber's Law, this paper proposes a simple, yet very powerful and robust local descriptor, called the Weber Local Descriptor (WLD). It is based on the fact that human perception of a pattern depends not only on the change of a stimulus (such as sound, lighting) but also on the original intensity of the stimulus. Specifically, WLD consists of two components: differential excitation and orientation. The differential excitation component is a function of the ratio between two terms: One is the relative intensity differences of a current pixel against its neighbors, the other is the intensity of the current pixel. The orientation component is the gradient orientation of the current pixel. For a given image, we use the two components to construct a concatenated WLD histogram. Experimental results on the Brodatz and KTH-TIPS2-a texture databases show that WLD impressively outperforms the other widely used descriptors (e.g., Gabor and SIFT). In addition, experimental results on human face detection also show a promising performance comparable to the best known results on the MIT+CMU frontal face test set, the AR face data set, and the CMU profile test set 
650 4 |a Journal Article 
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700 1 |a Shan, Shiguang  |e verfasserin  |4 aut 
700 1 |a He, Chu  |e verfasserin  |4 aut 
700 1 |a Zhao, Guoying  |e verfasserin  |4 aut 
700 1 |a Pietikäinen, Matti  |e verfasserin  |4 aut 
700 1 |a Chen, Xilin  |e verfasserin  |4 aut 
700 1 |a Gao, Wen  |e verfasserin  |4 aut 
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