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Texture segmentation is the process of partitioning an image into regionswith different textures containing a similar group of pixels. Detecting thediscontinuity of the filter's output and their statistical properties help insegmenting and classifying a given image with different texture regions. Inthis proposed paper, chili x-ray image texture segmentation is performed byusing Gabor filter. The texture segmented result obtained from Gabor filter fedinto three texture filters, namely Entropy, Standard Deviation and Rangefilter. After performing texture analysis, features can be extracted by usingStatistical methods. In this paper Gray Level Co-occurrence Matrices and Firstorder statistics are used as feature extraction methods. Features extractedfrom statistical methods are given to Support Vector Machine (SVM) classifier.Using this methodology, it is found that texture segmentation is followed bythe Gray Level Co-occurrence Matrix feature extraction method gives a higheraccuracy rate of 84% when compared with First order feature extraction method.  Key Words: Texture segmentation, Texture filter, Gabor filter, Featureextraction methods, SVM classifier.

Texture Based Image Segmentation of Chili Pepper X-Ray Images Using Gabor Filter