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Texture Segmentation using LBP embedded Region Competition
Xu, Qing (Shanghai Jiao tong University. Institute of Image Processing & Pattern Recognition)
Yang, Jie (Shanghai Jiao tong University. Institute of Image Processing & Pattern Recognition)
Ding, Siyi (Shanghai Jiao tong University. Institute of Image Processing & Pattern Recognition)

Fecha: 2005
Resumen: In this paper, we modify the region competition method to segment textures. First, local Binary pattern (LBP) histogram is adopted to capture the texture information. Then, considering the specific goal of texture segmentation, we propose new assumption about region competition and rewrite the energy function based on LBP histograms. We also develop the two-stage iterative algorithm to make our energy converge to a local minimum. Because of the fast LBP operator and nonparametric histogram model, we can simplify the step of parameter estimating, which is always the most time-consuming. Besides, LBP' s high performance for texture characterization helps to make our method more suitable for texture segmentation problem. Experiments show that the performance of our proposed method is promising, and a robust and fast segmentation of texture images is obtained.
Derechos: Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades. Creative Commons
Lengua: Anglès
Documento: Article ; recerca ; Versió publicada
Materia: Region competition ; Local binary pattern ; Competició de regió ; Model binari local ; Competición de región ; Modelo binario local
Publicado en: ELCVIA. Electronic letters on computer vision and image analysis, V. 5 n. 1 (2005) p. 41-47, ISSN 1577-5097

Adreça original: https://elcvia.cvc.uab.es/article/view/v5-n1-xu-yang-ding
Adreça alternativa: https://raco.cat/index.php/ELCVIA/article/view/31609
DOI: 10.5565/rev/elcvia.83


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