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Texture Image Segmentation Using in Gabor Filter and Artificial Neural Network

Shoba Rani, Dr.S. Purushothaman

Abstract


The work focuses on segmentation of various textures of a given image. In addition, retrieval of the desired component of the image is done. The segmentation and retrieval is based on the texture features of the image. The goal of the work is to develop a promising technique to segment the textures of the image. Basically,we use a set of GABOR filters segmenting the given image and using artificial neural network (ANN) for extracting the relevant information. The theme of the work is based on GABOR filters which are based
on the famous Gaussian function. Using Gabor filters, does the extractions of features of the various textures in the given image. By using the obtained features, subsequent labeling is done by (Backpropagation algorithm) ANN. The nature of the work involves taking an image texture as input and getting the partitioned or segmented textures as output. It can be very well justified in doing this work as automatic segmentation, identification and classification and as an important role image processing. The future of the work is unlimited.


Keywords


Texture Image Segmentation, Image Retrieval, Gabor Filters, Artificial Neural Network.

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References


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