Completed Local Ternary Pattern for Rotation Invariant Texture Classification
Despite the fact that the two texture descriptors, the completed modeling of Local Binary Pattern (CLBP) and the Completed Local Binary Count (CLBC), have achieved a remarkable accuracy for invariant rotation texture classification, they inherit some Local Binary Pattern (LBP) drawbacks. The LBP i...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi Publishing Corporation
2014
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| Subjects: | |
| Online Access: | http://eprints.usm.my/38476/ http://eprints.usm.my/38476/1/Completed_Local_Ternary_Pattern_for_Rotation_Invariant_Texture_Classification.pdf |
| _version_ | 1848878480269246464 |
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| author | Rassem, Taha H. Bee, Ee Khoo |
| author_facet | Rassem, Taha H. Bee, Ee Khoo |
| author_sort | Rassem, Taha H. |
| building | USM Institutional Repository |
| collection | Online Access |
| description | Despite the fact that the two texture descriptors, the completed modeling of Local Binary Pattern (CLBP) and the Completed
Local Binary Count (CLBC), have achieved a remarkable accuracy for invariant rotation texture classification, they inherit some
Local Binary Pattern (LBP) drawbacks. The LBP is sensitive to noise, and different patterns of LBP may be classified into the
same class that reduces its discriminating property. Although, the Local Ternary Pattern (LTP) is proposed to be more robust
to noise than LBP, however, the latter’s weakness may appear with the LTP as well as with LBP. In this paper, a novel completed
modeling of the Local Ternary Pattern (LTP) operator is proposed to overcome both LBP drawbacks, and an associated completed
Local Ternary Pattern (CLTP) scheme is developed for rotation invariant texture classification. The experimental results using four
different texture databases show that the proposed CLTP achieved an impressive classification accuracy as compared to the CLBP
and CLBC descriptors. |
| first_indexed | 2025-11-15T17:32:00Z |
| format | Article |
| id | usm-38476 |
| institution | Universiti Sains Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T17:32:00Z |
| publishDate | 2014 |
| publisher | Hindawi Publishing Corporation |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | usm-384762018-01-23T03:55:03Z http://eprints.usm.my/38476/ Completed Local Ternary Pattern for Rotation Invariant Texture Classification Rassem, Taha H. Bee, Ee Khoo TK1-9971 Electrical engineering. Electronics. Nuclear engineering Despite the fact that the two texture descriptors, the completed modeling of Local Binary Pattern (CLBP) and the Completed Local Binary Count (CLBC), have achieved a remarkable accuracy for invariant rotation texture classification, they inherit some Local Binary Pattern (LBP) drawbacks. The LBP is sensitive to noise, and different patterns of LBP may be classified into the same class that reduces its discriminating property. Although, the Local Ternary Pattern (LTP) is proposed to be more robust to noise than LBP, however, the latter’s weakness may appear with the LTP as well as with LBP. In this paper, a novel completed modeling of the Local Ternary Pattern (LTP) operator is proposed to overcome both LBP drawbacks, and an associated completed Local Ternary Pattern (CLTP) scheme is developed for rotation invariant texture classification. The experimental results using four different texture databases show that the proposed CLTP achieved an impressive classification accuracy as compared to the CLBP and CLBC descriptors. Hindawi Publishing Corporation 2014 Article PeerReviewed application/pdf en http://eprints.usm.my/38476/1/Completed_Local_Ternary_Pattern_for_Rotation_Invariant_Texture_Classification.pdf Rassem, Taha H. and Bee, Ee Khoo (2014) Completed Local Ternary Pattern for Rotation Invariant Texture Classification. Scientific World Journal, 2014 (373254). pp. 1-10. ISSN 2356-6140 http://dx.doi.org/10.1155/2014/373254 |
| spellingShingle | TK1-9971 Electrical engineering. Electronics. Nuclear engineering Rassem, Taha H. Bee, Ee Khoo Completed Local Ternary Pattern for Rotation Invariant Texture Classification |
| title | Completed Local Ternary Pattern for Rotation Invariant Texture Classification |
| title_full | Completed Local Ternary Pattern for Rotation Invariant Texture Classification |
| title_fullStr | Completed Local Ternary Pattern for Rotation Invariant Texture Classification |
| title_full_unstemmed | Completed Local Ternary Pattern for Rotation Invariant Texture Classification |
| title_short | Completed Local Ternary Pattern for Rotation Invariant Texture Classification |
| title_sort | completed local ternary pattern for rotation invariant texture classification |
| topic | TK1-9971 Electrical engineering. Electronics. Nuclear engineering |
| url | http://eprints.usm.my/38476/ http://eprints.usm.my/38476/ http://eprints.usm.my/38476/1/Completed_Local_Ternary_Pattern_for_Rotation_Invariant_Texture_Classification.pdf |