Estimating the Number of Clusters with Database for Texture Segmentation Using Gabor Filter

摘要

This paper addresses a novel solution of the problem of image segmentation by its texture using Gabor filter. Texture segmentation has been worked well by using Gabor filter, but there still is a problem; the number of clusters. There are several studies about estimating number of clusters with statistical approaches such as gap statistic. However, there are some problems to apply those methods to texture segmentation in terms of accuracy and time complexity. To overcome these limits, this paper proposes novel method to estimate optimal number of clusters for texture segmentation by using training dataset and several assumptions which are appropriate for image segmentation. We evaluate the proposed method on dataset consists of texture image and limit possible number of clusters from 2 to 5. And we also evaluate the proposed method by real image contains various texture such as rock stratum.