Multi-Scale Colour Completed Local Binary Patterns for Scene and Event Sport Image Categorisation
The Local Binary Pattern (LBP) texture descriptor and some of its variant descriptors have been successfully used for texture classification and for a few other tasks such as face recognition, facial expression, and texture segmentation. However, these descriptors have been barely used for image cat...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
International Association of Engineers (IAENG)
2017
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/17765/ http://umpir.ump.edu.my/id/eprint/17765/ http://umpir.ump.edu.my/id/eprint/17765/1/IJCS_44_2_09.pdf |
| Summary: | The Local Binary Pattern (LBP) texture descriptor and some of its variant descriptors have been successfully used for texture classification and for a few other tasks such as face recognition, facial expression, and texture segmentation. However, these descriptors have been barely used for image categorisation because their calculations are based on the gray image and they are only invariant to monotonic light variations on the gray level. These descriptors ignore colour information despite their key role in distinguishing the objects and the natural scenes. In this paper, we enhance the Completed Local Binary Pattern (CLBP), an LBP variant with an impressive performance on texture classification. We propose five multiscale colour CLBP (CCLBP) descriptors by incorporating five different colour information into the original CLBP. By using the Oliva and Torralba (OT8) and Event sport datasets, our results attest to the superiority of the proposed CCLBP descriptors over the original CLBP in terms of image categorisation. |
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