Article: Orthogonal opponent colour local binary patterns: a new colour-texture descriptor for content based-image retrieval Journal: International Journal of Computational Vision and Robotics (IJCVR) 2025 Vol.15 No.3 pp.351 - 378 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. Inderscience Publishers - linking academia, business and industry through research

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

Authors: Rahima Boukerma; Bachir Boucheham; Salah Bougueroua

Addresses: Department of Computer Science, Laboratoire de Recherche en Electronique de Skikda (LRES), 20 Août 1955 University of Skikda, DZ 21000 Skikda, Algeria ' Department of Computer Science, Laboratoire de Recherche en Electronique de Skikda (LRES), 20 Août 1955 University of Skikda, DZ 21000 Skikda, Algeria ' Department of Computer Science, Laboratoire de Recherche en Electronique de Skikda (LRES), 20 Août 1955 University of Skikda, DZ 21000 Skikda, Algeria

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.

Keywords: CBIR; IOCLBP; LBP; multichannel feature extraction; OCLBP; orthogonal-IOCLBP; orthogonal-OCLBP.

DOI: 10.1504/IJCVR.2025.146295

International Journal of Computational Vision and Robotics, 2025 Vol.15 No.3, pp.351 - 378

Received: 15 Nov 2022
Accepted: 15 Nov 2023
Published online: 19 May 2025 *

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

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