DocumentCode
598990
Title
Local self-Similarity based texture classification
Author
Hongbo Yang ; Xia Hou
Author_Institution
Autom. Sch., Beijing Inf. Sci. & Technol. Univ., Beijing, China
fYear
2012
fDate
16-18 Oct. 2012
Firstpage
795
Lastpage
799
Abstract
Aim of this paper is to develop a texture classification system for browsing and retrieval of image data. In this paper a novel local self-similarity texture descriptor is presented to describe the local texture pattern. And then, the classifier can be obtained by training local self-similarity texture descriptors captured from different textures. In this paper, the experiments are performed on the Brodatz texture database. And the results demonstrate that the proposed method is very efficient and can achieve high correct classification rate.
Keywords
fractals; image classification; image retrieval; image texture; visual databases; Brodatz texture database; image data browsing; image data retrieval; local self-similarity texture descriptors training; local self-similarity-based texture classification; local texture pattern; Algorithm design and analysis; Classification algorithms; Databases; Feature extraction; Gabor filters; Image segmentation; Training; AdaBoost; local self-similarity; texture classification;
fLanguage
English
Publisher
ieee
Conference_Titel
Image and Signal Processing (CISP), 2012 5th International Congress on
Conference_Location
Chongqing
Print_ISBN
978-1-4673-0965-3
Type
conf
DOI
10.1109/CISP.2012.6469914
Filename
6469914
Link To Document