Texture classification and retrieval using random neural network model

2004-03-30

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Texture classification and retrieval using random neural network model
Teke, Alper; Atalay, Mehmet Volkan; Department of Computer Engineering (2003)
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...
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This paper proposes a new maximum a posteriori (MAP) based super-resolution (SR) image reconstruction method targeting edges and textures in images. Unlike conventional MAP based SR image reconstruction methods a spatially varying image prior is employed which is updated according to the frequency content of the reconstructed image at each iteration at different locations. Two alternative methods based on discrete cosine transforms (DCT) and Gabor filters are proposed for determining the image prior. The pr...
Citation Formats
A. Teke and M. V. Atalay, “Texture classification and retrieval using random neural network model,” 2004, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/35264.