Texture Classification Using Scattering Statistical and Cooccurrence Features
Joint Authors
Wang, Juan
Zhao, Jie
Zhang, Jiang-She
Source
Mathematical Problems in Engineering
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-02-08
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
Texture classification is an important research topic in image processing.
In 2012, scattering transform computed by iterating over successive wavelet transforms and modulus operators was introduced.
This paper presents new approaches for texture features extraction using scattering transform.
Scattering statistical features and scattering cooccurrence features are derived from subbands of the scattering decomposition and original images.
And these features are used for classification for the four datasets containing 20, 30, 112, and 129 texture images, respectively.
Experimental results show that our approaches have the promising results in classification.
American Psychological Association (APA)
Wang, Juan& Zhang, Jiang-She& Zhao, Jie. 2016. Texture Classification Using Scattering Statistical and Cooccurrence Features. Mathematical Problems in Engineering،Vol. 2016, no. 2016, pp.1-6.
https://search.emarefa.net/detail/BIM-1112120
Modern Language Association (MLA)
Wang, Juan…[et al.]. Texture Classification Using Scattering Statistical and Cooccurrence Features. Mathematical Problems in Engineering No. 2016 (2016), pp.1-6.
https://search.emarefa.net/detail/BIM-1112120
American Medical Association (AMA)
Wang, Juan& Zhang, Jiang-She& Zhao, Jie. Texture Classification Using Scattering Statistical and Cooccurrence Features. Mathematical Problems in Engineering. 2016. Vol. 2016, no. 2016, pp.1-6.
https://search.emarefa.net/detail/BIM-1112120
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1112120