Experimental methodology for performance characterization of a line detection algorithm
Tapas Kanungo, Mysore Y. Jaisimha, Robert M. Haralick, John C. Palmer · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1991
We present a general methodology for designing experiments to quantitatively characterize lowlevel computer vision algorithms. The methodology can be applied to any vision problem that can be posed as a detection task. It provides a convenient framework to measure the sensitivity of an algorithm to various factors that affect the performance. The methodology is illustrated by applying it to a line detection algorithm consisting of the second directional derivative edge detector followed by a Hough transform. In particular we measure the selectivity of the algorithm in the presence of an interfering oriented grating and additive Gaussian noise. The final result is a measure of the detectors'' performance as a function of the orientation of the interfering grating.