Maximization of contour edge detection using adaptive thresholding

Michelle Van Dyke-Lewis; Arthur Robert Weeks; Harley R. Myler

doi:10.1117/12.154995

3 September 1993 Maximization of contour edge detection using adaptive thresholding

Michelle Van Dyke-Lewis, Arthur Robert Weeks, Harley R. Myler

Proceedings Volume 1955, Signal Processing, Sensor Fusion, and Target Recognition II; (1993) https://doi.org/10.1117/12.154995
Event: Optical Engineering and Photonics in Aerospace Sensing, 1993, Orlando, FL, United States

Abstract

A new adaptive thresholding technique is presented that maximizes the contour edge information within an image. Early work by Attneave suggested that visual information in images is concentrated at the contours. He concluded that the information associated with these points and their nearby neighbors is essential for image perception. Resnikoff has suggested a measurement of information gain in terms of direction. This measurement determines information gained from a measure of an angle direction along image contours relative to other measures of information gain for other positions along the curve. Hence, one form of information measure is the angular entropy of contours within an image. Our adaptive thresholding algorithm begins by varying the threshold value between a minimum and a maximum threshold value and then computing the total contour entropy over the entire binarized edge image. Next, the threshold value that yields the highest contour entropy is selected as the optimum threshold value. It is at this threshold value that the binarized image contains the greatest amount of image features.

Citation Download Citation

Michelle Van Dyke-Lewis, Arthur Robert Weeks, and Harley R. Myler "Maximization of contour edge detection using adaptive thresholding", Proc. SPIE 1955, Signal Processing, Sensor Fusion, and Target Recognition II, (3 September 1993); https://doi.org/10.1117/12.154995

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