|Table of Contents|

[1] Wu Jiasong, Jiang Longyu, Han Xu, et al. Performance evaluation of wavelet scattering networkin image texture classification in various color spaces [J]. Journal of Southeast University (English Edition), 2015, 31 (1): 46-50. [doi:10.3969/j.issn.1003-7985.2015.01.008]
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Performance evaluation of wavelet scattering networkin image texture classification in various color spaces()
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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:
31
Issue:
2015 1
Page:
46-50
Research Field:
Computer Science and Engineering
Publishing date:
2015-03-30

Info

Title:
Performance evaluation of wavelet scattering networkin image texture classification in various color spaces
Author(s):
Wu Jiasong1;  4;  Jiang Longyu1;  4;  Han Xu1;  4;  Lotfi Senhadji2;  3;  4;  Shu Huazhong1;  4
1Key Laboratory of Computer Network and Information Integration of Ministry of Education, Southeast University, Nanjing 210096, China
2Institut National de la Santé et de la Recherche Médicale U 1099, Rennes 35000, France
3Laboratoire Traitement du Signal et de l’Image, Université de Rennes 1, Rennes 35000, France
4Centre de Recherche en Information Biomédicale Sino-français, Southeast University, Nanjing 210096, China
Keywords:
wavelet scattering network;  color texture classification;  color spaces;  opponent mechanism
PACS:
TP391
DOI:
10.3969/j.issn.1003-7985.2015.01.008
Abstract:
The optimized color space is searched by using the wavelet scattering network in the KTH_TIPS_COL color image database for image texture classification. The effect of choosing the color space on the classification accuracy is investigated by converting red green blue(RGB)color space to various other color spaces. The results show that the classification performance generally changes to a large degree when performing color texture classification in various color spaces, and the opponent RGB-based wavelet scattering network outperforms other color spaces-based wavelet scattering networks. Considering that color spaces can be changed into each other, therefore, when dealing with the problem of color texture classification, converting other color spaces to the opponent RGB color space is recommended before performing the wavelet scattering network.

References:

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Memo

Memo:
Biography: Wu Jiasong(1983—), male, doctor, lecturer, jswu@seu.edu.cn.
Foundation items: The National Basic Research Program of China(No.2011CB707904), the National Natural Science Foundation of China(No.61201344, 61271312, 11301074), the Natural Science Foundation of Jiangsu Province(No.BK2012329), the Specialized Research Fund for the Doctoral Program of Higher Education(No.20110092110023, 20120092120036).
Citation: Wu Jiasong, Jiang Longyu, Han Xu, et al. Performance evaluation of wavelet scattering network in image texture classification in various color spaces[J].Journal of Southeast University(English Edition), 2015, 31(1):46-50.[doi:10.3969/j.issn.1003-7985.2015.01.008]
Last Update: 2015-03-20