Texture classification and retrieval using random neural network model

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2003
Teke, Alper
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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.
Neural networks (Computer science), Remote sensing
http://etd.lib.metu.edu.tr/upload/1089317/index.pdf
https://hdl.handle.net/11511/13974
Graduate School of Natural and Applied Sciences, Thesis

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Citation Formats
A. Teke, “Texture classification and retrieval using random neural network model,” M.S. - Master of Science, Middle East Technical University, 2003.
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