Experimental methodology for performance characterization of a line detection algorithm

Tapas Kanungo; Mysore Y. Jaisimha; Robert M. Haralick; John Palmer

doi:10.1117/12.25352

1 March 1991 Experimental methodology for performance characterization of a line detection algorithm

Tapas Kanungo, Mysore Y. Jaisimha, Robert M. Haralick, John Palmer

Proceedings Volume 1385, Optics, Illumination, and Image Sensing for Machine Vision V; (1991) https://doi.org/10.1117/12.25352
Event: Advances in Intelligent Robotics Systems, 1990, Boston, MA, United States

Abstract

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.

Citation Download Citation

Tapas Kanungo, Mysore Y. Jaisimha, Robert M. Haralick, and John Palmer "Experimental methodology for performance characterization of a line detection algorithm", Proc. SPIE 1385, Optics, Illumination, and Image Sensing for Machine Vision V, (1 March 1991); https://doi.org/10.1117/12.25352

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