Sparse presentation based classification with position-weighted block dictionary

Jun He; Tian Zuo; Bo Sun; Xuewen Wu; Lejun Yu; Fengxiang Ge; Chao Chen

doi:10.1117/12.2039610

25 February 2014 Sparse presentation based classification with position-weighted block dictionary

Jun He, Tian Zuo, Bo Sun, Xuewen Wu, Lejun Yu, Fengxiang Ge, Chao Chen

Proceedings Volume 9019, Image Processing: Algorithms and Systems XII; 90190X (2014) https://doi.org/10.1117/12.2039610
Event: IS&T/SPIE Electronic Imaging, 2014, San Francisco, California, United States

Abstract

This paper is aiming at applying sparse representation based classification (SRC) on general objects of a certain scale. Authors analyze the characteristics of general object recognition and propose a position-weighted block dictionary (PWBD) based on sparse presentation and design a framework of SRC with it (PWBD-SRC). Principle and implementation of PWBD-SRC have been introduced in the article, and experiments on car models have been given in the article. From experimental results, it can be seen that with position-weighted block dictionary (PWBD) not only the dictionary scale can be effectively reduced, but also roles of image blocks taking in representing a whole image can be embodied to a certain extent. In reorganization application, an image only containing partial objects can be identified with PWBD-SRC. Besides, rotation and perspective robustness can be achieved. Finally, a brief description on some remaining problems has been proposed in the article.

Citation Download Citation

Jun He, Tian Zuo, Bo Sun, Xuewen Wu, Lejun Yu, Fengxiang Ge, and Chao Chen "Sparse presentation based classification with position-weighted block dictionary", Proc. SPIE 9019, Image Processing: Algorithms and Systems XII, 90190X (25 February 2014); https://doi.org/10.1117/12.2039610

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