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Gray-level Texture Characterization Based on a New Adaptive Nonlinear Auto-Regressive Filter
Sayadi, Mounir (ESSTT. SICISI Unit (Tunísia))
Sakrani, Samir (ESSTT. SICISI Unit (Tunísia))
Fnaiech, Farhat (ESSTT. SICISI Unit (Tunísia))
Cheriet, Mohamed (École de technologie supérieure, Notre-Dame (Montreal, Canadà))

Data: 2008
Resum: In this paper, we propose a new nonlinear exponential adaptive two-dimensional (2-D) filter for texture characterization. The filter coefficients are updated with the Least Mean Square (LMS) algorithm. The proposed nonlinear model is used for texture characterization with a 2-D Auto-Regressive (AR) adaptive model. The main advantage of the new nonlinear exponential adaptive 2-D filter is the reduced number of coefficients used to characterize the nonlinear parametric models of images regarding the 2-D second-order Volterra model. Whatever the degree of the non-linearity, the problem results in the same number of coefficients as in the linear case. The characterization efficiency of the proposed exponential model is compared to the one provided by both 2-D linear and Volterra filters and the cooccurrence matrix method. The comparison is based on two criteria usually used to evaluate the features discriminating ability and the class quantification. Extensive experiments proved that the exponential model coefficients give better results in texture discrimination than several other parametric features even in a noisy context.
Drets: Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial 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
Llengua: Anglès.
Document: article ; recerca ; publishedVersion
Matèria: Image Analysis ; 2-D nonlinear filter ; 2-D adaptive filter ; Texture characterization ; Anàlisi d'imatge ; 2-D de filtre no lineal ; 2-D filtre adaptable ; Caracterització de textures ; Análisis de imagen ; 2-D de filtro no lineal ; 2-D filtro adaptable ; Caracterización de texturas
Publicat a: ELCVIA : Electronic Letters on Computer Vision and Image Analysis, V. 7 n. 1 (2008) p. 40-53, ISSN 1577-5097

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