Digital image processing (2nd ed.)
Digital image processing (2nd ed.)
A probabilistic Hough transform
Pattern Recognition
Randomized Hough transform (RHT): basic mechanisms, algorithms, and computational complexities
CVGIP: Image Understanding
A real-time hardware implementation of the Hough transform
Journal of Systems Architecture: the EUROMICRO Journal
Use of the Hough transformation to detect lines and curves in pictures
Communications of the ACM
Design and Integration of Parallel Hough-Transform Chips for High-speed Line Detection
ICPADS '05 Proceedings of the 11th International Conference on Parallel and Distributed Systems - Workshops - Volume 02
Finding Picture Edges Through Collinearity of Feature Points
IEEE Transactions on Computers
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Non-collinear edge pixels are equivalent to noise for the linear Hough transform (LHT). Existing methods that reduce the number of points for Hough voting are based on random and/or probabilistic selection. Such methods select both collinear and noisy pixels, thereby incurring unwanted computational costs. In this paper, we propose a novel gradient angle histogram based technique to generate modified straight line edge map (SLEM), which largely retains the straight line edges and eliminates noisy edge pixels. A block-based SLEM generation is proposed to increase the robustness of straight line extraction and validated on test images. Further, effect of varying block sizes on accuracy of straight line detection is studied and appropriate block settings are derived. The proposed gradient angle histogram based method reduces the number of edge pixels by as much as 85%.