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Optical Engineering

Fast weighted K-view-voting algorithm for image texture classification
Author(s): Hong Liu; Yihua Lan; Renchao Jin; Enmin Song; Qian Wang; Chih-Cheng Hung
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Paper Abstract

We propose an innovative and efficient approach to improve K-view-template (K-view-T) and K-view-datagram (K-view-D) algorithms for image texture classification. The proposed approach, called the weighted K-view-voting algorithm (K-view-V), uses a novel voting method for texture classification and an accelerating method based on the efficient summed square image (SSI) scheme as well as fast Fourier transform (FFT) to enable overall faster processing. Decision making, which assigns a pixel to a texture class, occurs by using our weighted voting method among the "promising" members in the neighborhood of a classified pixel. In other words, this neighborhood consists of all the views, and each view has a classified pixel in its territory. Experimental results on benchmark images, which are randomly taken from Brodatz Gallery and natural and medical images, show that this new classification algorithm gives higher classification accuracy than existing K-view algorithms. In particular, it improves the accurate classification of pixels near the texture boundary. In addition, the proposed acceleration method improves the processing speed of K-view-V as it requires much less computation time than other K-view algorithms. Compared with the results of earlier developed K-view algorithms and the gray level co-occurrence matrix (GLCM), the proposed algorithm is more robust, faster, and more accurate.

Paper Details

Date Published: 2 March 2012
PDF: 13 pages
Opt. Eng. 51(2) 027004 doi: 10.1117/1.OE.51.2.027004
Published in: Optical Engineering Volume 51, Issue 2
Show Author Affiliations
Hong Liu, Huazhong Univ. of Science and Technology (China)
Yihua Lan, Huazhong Univ. of Science and Technology (China)
Renchao Jin, Huazhong Univ. of Science and Technology (China)
Enmin Song, Huazhong Univ. of Science and Technology (China)
Qian Wang, Zhongnan Univ. of Economics and Law (China)
Chih-Cheng Hung, Southern Polytechnic State Univ. (United States)


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