Quantized image patches co-occurrence matrix: a new statistical approach for texture classification using image patch exemplars

Zhonghua Liu; Jingyan Wang; Yongping Li; Ying Zhang; Chao Wang

doi:10.1117/12.896155

8 July 2011 Quantized image patches co-occurrence matrix: a new statistical approach for texture classification using image patch exemplars

Zhonghua Liu, Jingyan Wang, Yongping Li, Ying Zhang, Chao Wang

Author Affiliations +

Proceedings Volume 8009, Third International Conference on Digital Image Processing (ICDIP 2011); 80092P (2011) https://doi.org/10.1117/12.896155
Event: 3rd International Conference on Digital Image Processing, 2011, Chengdu, China

Abstract

The statistical distribution of image patch exemplars has been shown to be an effective approach to texture classification. In this paper, the joint distribution of pairs of patches for texture classification from single images is investigated. We developed a statistical method of examining texture that considers the spatial relationship of image patches, which is called the quantized patches co-occurrence matrix (QPCM). In our method, the images are first slipt into small image patches, and then the patches are quantized to the closest patch cluster centers (textons) which is learned form training images. By calculating how often pairs of patches with specific quantized values (texton labels) and in a specified spatial relationship occur in an image, we create the QPCM for images representation. Moreover, we developed a fusion framework for texture classification by fusing 4 QPCM functions with specified neighboring spatial relationship and 3 other statistical representations of image patches, which is called QPCM-SVM classifier. The effectiveness of the proposed texture classification methodology is demonstrated via an extensive consistent evaluation in standard benchmarks that clearly shows better performance against state-of-the-art statistical approach using image patch exemplars.

Citation Download Citation

Zhonghua Liu, Jingyan Wang, Yongping Li, Ying Zhang, and Chao Wang "Quantized image patches co-occurrence matrix: a new statistical approach for texture classification using image patch exemplars", Proc. SPIE 8009, Third International Conference on Digital Image Processing (ICDIP 2011), 80092P (8 July 2011); https://doi.org/10.1117/12.896155

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available