Vanishing-Point Detection Based on a Fuzzy Clustering Algorithm and New Clustering Validity Measure

Chien-Hsing  Chou; Yu-Xiang  Zhao; Hsien-Pang Tai

doi:10.6180/jase.2015.18.2.02

Vanishing-Point Detection Based on a Fuzzy Clustering Algorithm and New Clustering Validity Measure

Computer Science and Information Engineering

Chien-Hsing Chou This email address is being protected from spambots. You need JavaScript enabled to view it.¹, Yu-Xiang Zhao² and Hsien-Pang Tai¹

¹Department of Electrical Engineering, Tamkang University, Tamsui, Taiwan 251, R.O.C.
²Department of Computer Science & Information Engineering, National Quemoy University, Quemoy, Taiwan 892, R.O.C.

Received: November 3, 2014
Accepted: April 16, 2015
Publication Date: June 1, 2015

Download Citation: ||https://doi.org/10.6180/jase.2015.18.2.02

ABSTRACT

This paper proposes an image-preprocessing method combined with a fuzzy clustering algorithm and new validity measure to detect the vanishing point in an image. The proposed method segments the object in an image by using the clustering algorithm and then extracts critical vanishing lines. By examining the intersection of the vanishing lines, the vanishing point is located. To locate the vanishing point accurately, the initial cluster number of the fuzzy clustering algorithm should be provided correctly. Therefore, the study proposes a new clustering validity measure, the area measure, to estimate the initial cluster number according to the information of cluster areas. Experimental results on 29 images show that the proposed preprocessing method and validity measure can accurately identify the location of the vanishing point and vanishing lines. In addition, compared with several validity measures, the new validity measure achieves satisfactory experimental results and outperforms six other validity measures.

Keywords: Fuzzy Clustering, Clustering Validity, Vanishing Point, Vanishing Line, Depth Map

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