Texture Segmentation Using the Mixtures of Principal Component Analyzers

Musa, Mohamed E. M.; Duin, Robert P. W.; Ridder, Dick de; Atalay, Volkan

doi:10.1007/978-3-540-39737-3_63

Cited by 3 publications

References 9 publications

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Texture Classification and Retrieval Using the Random Neural Network Model

Teke

Atalay

2006

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Texture is one of the most important characteristics used in computer vision and image processing applications. In this thesis, a new texture classification and retrieval method is proposed for texture analysis applications. The technique makes use of the random neural network model and it is supervised. The main aim is to represent textures with parameters which are the random neural network weights and classify and retrieve textures using this texture definition. The network has neurons that correspond to each image pixel, and the neurons are connected according to neighboring relationship between pixels. The method is tested on artificial images produced by using Brodatz album and texture blocks cut from remotely sensed imagery.

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Texture Classification and Retrieval Using the Random Neural Network Model

Teke

Atalay

2006

CMS

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Texture classification and retrieval using random neural network model

Teke

Atalay

6th IEEE Southwest Symposium on Image Analysis and Interpretation, 2004.

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, 45 pages Texture is one of the most important characteristics used in computer vision and image processing applications. In this thesis, a new texture classification and retrieval method is proposed for texture analysis applications. The technique makes use of the random neural network model and it is supervised. The main aim is to represent textures with parameters which are the random neural network weights and classify and retrieve textures using this texture definition. The network has neurons that correspond to each image pixel, and the neurons are connected according to neighboring relationship between pixels. The method is tested on artificial images produced by using Brodatz album and texture blocks cut from remotely sensed imagery.

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