TY - JOUR
T1 - Fast and robust techniques for detecting straight line segments using local models
AU - Shpilman, Ron
AU - Brailovsky, Victor
PY - 1999/9/20
Y1 - 1999/9/20
N2 - A new line parameterization model, based on Hough transform, offers robust identification of straight lines using geometrical features of lines. The article presents a new algorithm, based on this model, that achieves fast linear (in the number of edge points) detection of line segments, using a fixed small one-dimensional parameter space. The work provides schemes for easy parallel processing and prediction accelaration. The work also suggests a novel contour segmentation technique for filtering out outlier noise, and linking contour edge points at linear time. Results on several real and synthetic images are demonstrated and compared with Random Hough Transform.
AB - A new line parameterization model, based on Hough transform, offers robust identification of straight lines using geometrical features of lines. The article presents a new algorithm, based on this model, that achieves fast linear (in the number of edge points) detection of line segments, using a fixed small one-dimensional parameter space. The work provides schemes for easy parallel processing and prediction accelaration. The work also suggests a novel contour segmentation technique for filtering out outlier noise, and linking contour edge points at linear time. Results on several real and synthetic images are demonstrated and compared with Random Hough Transform.
KW - Contour segmentation
KW - Embedded computations
KW - Fast line detection
KW - Hough transform
KW - Parallel scheme
UR - http://www.scopus.com/inward/record.url?scp=0033454036&partnerID=8YFLogxK
U2 - 10.1016/S0167-8655(99)00051-3
DO - 10.1016/S0167-8655(99)00051-3
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AN - SCOPUS:0033454036
SN - 0167-8655
VL - 20
SP - 865
EP - 877
JO - Pattern Recognition Letters
JF - Pattern Recognition Letters
IS - 9
ER -