We propose a texture analysis method based on Rényi’s entropies. The method aims at identifying texels in regular textures by searching for the smallest window through which the minimum number of different visual patterns is observed when moving the window over a given texture. The experimental results show that any of Rényi’s entropies can be used for texel identification. However, the second order entropy, due to its robust estimation, is the most reliable. The main advantages of the proposed method are its robustness and its flexibility. We illustrate the usefulness and the effectiveness of the method in a texture synthesis application and we compare it with other structural approaches
Element-based textures are a kind of texture formed by nameable elements, thetexels [1], distributed...
We discuss entropy characteristics used in various research techniques for investigation of complex ...
Appearance description is a relevant field in computer vision that enables object recognition in dom...
We propose a texture analysis method based on Rényi’s entropies. The method aims at identifying texe...
We propose a texture analysis method based on Rényi’s generalized entropies. The method aims at iden...
We propose a texture analysis method based on Renyi's generalized entropies. The method aims at iden...
Abstract. Texture periodicity and texture element (texel) size are important characteristics for tex...
Regular textures can be modelled as consisting of periodic patterns where a fundamental unit, or tex...
Capturing the essence of a textile image in a robust way is important to retrieve it in a large repo...
International audienceTwo-dimensional sample entropy (SampEn2D) has been recently proposed to quanti...
This paper proposes the problem of unsupervised extraction of texture elements, called texels, which...
An approach to the analysis of images of regular texture is proposed in which lattice hypotheses are...
In this paper we propose a new method to detect the global scale of images with regular, near regula...
Random textures are notoriously more difficult to deal with than regular textures particularly when ...
This paper presents a robust method for defect detection in textures, entropy-based automatic select...
Element-based textures are a kind of texture formed by nameable elements, thetexels [1], distributed...
We discuss entropy characteristics used in various research techniques for investigation of complex ...
Appearance description is a relevant field in computer vision that enables object recognition in dom...
We propose a texture analysis method based on Rényi’s entropies. The method aims at identifying texe...
We propose a texture analysis method based on Rényi’s generalized entropies. The method aims at iden...
We propose a texture analysis method based on Renyi's generalized entropies. The method aims at iden...
Abstract. Texture periodicity and texture element (texel) size are important characteristics for tex...
Regular textures can be modelled as consisting of periodic patterns where a fundamental unit, or tex...
Capturing the essence of a textile image in a robust way is important to retrieve it in a large repo...
International audienceTwo-dimensional sample entropy (SampEn2D) has been recently proposed to quanti...
This paper proposes the problem of unsupervised extraction of texture elements, called texels, which...
An approach to the analysis of images of regular texture is proposed in which lattice hypotheses are...
In this paper we propose a new method to detect the global scale of images with regular, near regula...
Random textures are notoriously more difficult to deal with than regular textures particularly when ...
This paper presents a robust method for defect detection in textures, entropy-based automatic select...
Element-based textures are a kind of texture formed by nameable elements, thetexels [1], distributed...
We discuss entropy characteristics used in various research techniques for investigation of complex ...
Appearance description is a relevant field in computer vision that enables object recognition in dom...