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학술대회 Estimating the Number of Clusters with Database for Texture Segmentation Using Gabor Filter
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저자
김민규, 임정묵, 신희숙, 오창목, 정현태
발행일
201507
출처
International Conference on Computer Vision Systems (ICVS) 2015 (LNCS 9163), pp.435-44
ISSN
0302-9743
DOI
https://dx.doi.org/10.1007/978-3-319-20904-3_39
협약과제
14MS9200, (통합)인간친화형 디바이스(스킨패치, 멀티모달 서피스) 및 디바이스 소셜 프레임워크 기술 개발, 배창석
초록
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.
키워드
Gabor filter, Number of clusters, Texture segmentation, Weight optimization
KSP 제안 키워드
Gabor filters, Gap statistic, Optimal number of clusters, Texture image, Time Complexity, Weight optimization, image segmentation, novel method, statistical approach, texture segmentation