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Analysis of Straight Line Detection Using PCA
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 Title & Authors
Analysis of Straight Line Detection Using PCA
Oh, Jeong-su;
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This paper analyzes the straight line detection using the principal component analysis (PCA) and proposes its improved algorithm to which two new functions are added. The first function removes invalid pixels through the detected straight line and detects a line again. The second function detects lines from non-overlapped blocks, selects valid line candidates, and detects a valid line from pixels adjacent to each line candidate. The proposed algorithm detects a more accurate straight line with a low computation in comparison with the conventional algorithm in an image with somewhat refined lines.
straight line detection;PCA;segmentation;eigen value;eigen vector;
 Cited by
R. C. Gonzalez, and R. E. Wood, Digital Image Processing, Prentice Hall, 2008.

A. McAndrew, Introduction to Digital Image Processing with MATLAB, Course Technology, 2004.

V. Hardzeyeu and F. Klefenz, “On using the hough transform for driving assistance applications,” in Proc. 4th Int. Conf. Intell. Comput. Commun. Process., pp.91–98, 2008.

R. O. Duda, and P. E. Hart. "Use of the Hough transformation to detect lines and curves in pictures," Communications of the ACM Vol. 15, No. 1, pp. 11-15, 1972. crossref(new window)

S. Guo, T. Pridmore, Y. Kong, and X. Zhang, “An improved Hough transform voting scheme utilizing surround suppression,” Pattern Recognition Letters, Vol. 30, No. 13, pp. 1241-1252, 2009. crossref(new window)

L. Smith, A Tutorial on Principal Components Analysis,, 2002.

J. Shlens. A tutorial on principal component analysis,, 2005.

Ilsuk Oh, Pattern Recognition, Kyobo Book, 2008.

Hakyong Han, Introduce to Pattern Recognition, Hanbit Media, 2009.