Orthogonal opponent colour local binary patterns: a new colour-texture descriptor for content based-image retrieval

Opponent colour local binary patterns (OCLBP) is one of the first extensions of greyscale LBP to colour images, which has been proven to be an effective descriptor for extracting colour texture features. In order to improve the OCLBP performance for image retrieval and increase its invariance to illumination change, we propose in this paper a new scheme for computing the OCLBP's inter-channel features. Unlike OCLBP, where the inter-channel features are computed by considering the circular neighbouring of the centre pixel, our proposed descriptor named orthogonal OCLBP (O-OCLBP) is constructed by considering the orthogonal neighbouring of the centre pixel. Moreover, the proposed scheme is applied to the improved version of OCLBP (IOCLBP) to derive a new descriptor named orthogonal IOCLBP (O-IOCLBP). Experiments performed over eight databases demonstrate that the proposed descriptors significantly improve retrieval performance on almost all databases, and show generally better results compared to some of the state-of-the-art descriptors.

Authors

Institutions

Publication Details

Journal
International Journal of Computational Vision and Robotics
Published
2025-01-01
DOI
https://doi.org/10.1504/ijcvr.2025.146295
Primary Topic
Image Retrieval and Classification Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Orthogonal opponent colour local binary patterns: a new colour-texture descriptor for content based-image retrieval

Rahima Boukerma, Salah Bougueroua, Bachir Boucheham
International Journal of Computational Vision and Robotics
Image Retrieval and Classification Techniques
article

Orthogonal opponent colour local binary patterns: a new colour-texture descriptor for content based-image retrieval

Rahima Boukerma, Salah Bougueroua, Bachir Boucheham
article en

Abstract

Opponent colour local binary patterns (OCLBP) is one of the first extensions of greyscale LBP to colour images, which has been proven to be an effective descriptor for extracting colour texture features. In order to improve the OCLBP performance for image retrieval and increase its invariance to illumination change, we propose in this paper a new scheme for computing the OCLBP's inter-channel features. Unlike OCLBP, where the inter-channel features are computed by considering the circular neighbouring of the centre pixel, our proposed descriptor named orthogonal OCLBP (O-OCLBP) is constructed by considering the orthogonal neighbouring of the centre pixel. Moreover, the proposed scheme is applied to the improved version of OCLBP (IOCLBP) to derive a new descriptor named orthogonal IOCLBP (O-IOCLBP). Experiments performed over eight databases demonstrate that the proposed descriptors significantly improve retrieval performance on almost all databases, and show generally better results compared to some of the state-of-the-art descriptors.

International Journal of Computational Vision and RoboticsVol. 15(3)
University of Skikda (DZ)
Openalex Percentile: Top 91%
Image Retrieval and Classification Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Orthogonal opponent colour local binary patterns: a new colour-texture descriptor for content based-image retrieval — Rahima Boukerma, Salah Bougueroua, et al. · International Journal of Computational Vision and Robotics (2025) | TGRS Research Map | TGRS