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Finding line segments by stick growing

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1 Author(s)
R. C. Nelson ; Dept. of Comput. Sci., Rochester Univ., NY, USA

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

Published in:

IEEE Transactions on Pattern Analysis and Machine Intelligence  (Volume:16 ,  Issue: 5 )