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Issue No.05 - May (1994 vol.16)
pp: 519-523
ABSTRACT
<p>A method is described for extracting lineal features from an image using extended local information to provide robustness and sensitivity. The method utilizes both gradient magnitude and direction information, and incorporates explicit lineal and end-stop terms. These terms are combined nonlinearly to produce an energy landscape in which local minima correspond to lineal features called sticks that can be represented as line segments. A hill climbing (stick-growing) process is used to find these minima. The method is compared to two others, and found to have improved gap-crossing characteristics.</p>
INDEX TERMS
image segmentation; feature extraction; line segment finding; stick growing; lineal feature extraction; extended local information; robustness; sensitivity; end-stop terms; hill climbing
CITATION
R.C. Nelson, "Finding Line Segments by Stick Growing", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.16, no. 5, pp. 519-523, May 1994, doi:10.1109/34.291445
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