A straight line detection using principal component analysis

Authors:
Yun-Seok Lee;Han-Suh Koo;Chang-Sung Jeong
Affiliations:
Department of Electronics Engineering, Korea University, Anam-Dong, Seongbuk-Gu, Seoul, Republic of Korea;Department of Electronics Engineering, Korea University, Anam-Dong, Seongbuk-Gu, Seoul, Republic of Korea;Department of Electronics Engineering, Korea University, Anam-Dong, Seongbuk-Gu, Seoul, Republic of Korea
Venue:
Pattern Recognition Letters
Year:
2006

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Abstract

A straight line detection algorithm is presented. The algorithm separates row and column edges from edge image using their primitive shapes. The edges are labeled, and the principal component analysis (PCA) is performed for each labeled edges. With the principal components, the algorithm detects straight lines and their orientations, which is useful for various intensive applications. Our algorithm overcomes the disadvantages of Hough transform (HT) and other algorithms, i.e. unknown grouping of collinear lines, complexity and local ambiguities. The experimental results show the efficiency of our algorithm.