Adjacent Local Binary Patterns Based on Color Space Fusion for Color Image Classification

Adjacent Local Binary Patterns Based on Color Space Fusion for Color Image Classification

Year:    2015

Journal of Fiber Bioengineering and Informatics, Vol. 8 (2015), Iss. 4 : pp. 783–790

Abstract

In this paper, we propose an improved image feature descriptor based on Local Binary Pattern, which is called Adjacent Local Binary Patterns based on Color Space Fusion (ALBPCSF). The proposed method fuses color feature and spatial relations. ALBPCSF uses the channel values of RGB and HSV color spaces to calculate the color feature. Then the proposed method considers the spatial relations which will be combined with the color feature. Finally, an image classification system framework based on ALBPCSF is given. In order to validate the performance, our method is compared with previous methods on Corel 1000 and MIT Vision Texture datasets. The results show that our approach is superior than other methods in color image classification.

You do not have full access to this article.

Already a Subscriber? Sign in as an individual or via your institution

Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/10.3993/jfbim00188

Journal of Fiber Bioengineering and Informatics, Vol. 8 (2015), Iss. 4 : pp. 783–790

Published online:    2015-01

AMS Subject Headings:   

Copyright:    COPYRIGHT: © Global Science Press

Pages:    8

Keywords:    Local Binary Pattern