NDLI: A Hough Transform based line detection method utilizing improved voting scheme

Content Provider	IEEE Xplore Digital Library
Author	Chang Huayao Wang Junzheng Wang Lipeng
Copyright Year	2010
Description	Author affiliation: School of Automation, Beijing Institute of Technology, 100081, China (Chang Huayao; Wang Junzheng; Wang Lipeng)
Abstract	Detecting lines from a digital image is an important step in many applications. The Hough Transform (HT) is a powerful tool for line extraction due to its global vision and robustness in noisy and degraded environment. Aiming at solving the problems associated with the HT: the heavy computational cost and considerable degeneration in performance, a new method utilizing improved voting scheme for the HT is proposed. By separating the edge pixels into clusters of approximately collinear pixels, linear regression is used to find the orientation of each cluster. Judged by the value of determination coefficient, clusters are chosen for voting directly or voting around its main orientation. Gaussian blur is used in peak detection for reducing adjacent peaks. Experimental results show efficiency of the proposed method in terms of detection rate, time and memory saving, and the robustness to spurious lines.
Starting Page	2857
Ending Page	2860
File Size	309152
Page Count	4
File Format	PDF
ISBN	9781424462636
e-ISBN	9787894631046
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-07-29
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Chinese Association of Aut
Subject Keyword	Image segmentation Image edge detection Determination Coefficient Line Detection Transforms Hough Transform Robustness Pattern recognition Joining processes Pixel
Content Type	Text
Resource Type	Article

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