Adjacent Local Binary Patterns Based on Color Space Fusion for Color Image Classification
DOI:
10.3993/jfbim00188
Journal of Fiber Bioengineering & Informatics, 8 (2015), pp. 783-790.
Published online: 2015-08
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@Article{JFBI-8-783,
author = {Shengsheng Wang, Dezhi Huang, Haiyang Jia, Dong Li and Bolou Bolou Dickson},
title = {Adjacent Local Binary Patterns Based on Color Space Fusion for Color Image Classification},
journal = {Journal of Fiber Bioengineering and Informatics},
year = {2015},
volume = {8},
number = {4},
pages = {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.},
issn = {2617-8699},
doi = {https://doi.org/10.3993/jfbim00188},
url = {http://global-sci.org/intro/article_detail/jfbi/4760.html}
}
TY - JOUR
T1 - Adjacent Local Binary Patterns Based on Color Space Fusion for Color Image Classification
AU - Shengsheng Wang, Dezhi Huang, Haiyang Jia, Dong Li & Bolou Bolou Dickson
JO - Journal of Fiber Bioengineering and Informatics
VL - 4
SP - 783
EP - 790
PY - 2015
DA - 2015/08
SN - 8
DO - http://doi.org/10.3993/jfbim00188
UR - https://global-sci.org/intro/article_detail/jfbi/4760.html
KW - Local Binary Pattern
KW - Color Texture
KW - KNN
KW - Image Classification
AB - 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.
Shengsheng Wang, Dezhi Huang, Haiyang Jia, Dong Li and Bolou Bolou Dickson. (2015). Adjacent Local Binary Patterns Based on Color Space Fusion for Color Image Classification.
Journal of Fiber Bioengineering and Informatics. 8 (4).
783-790.
doi:10.3993/jfbim00188
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