Fast contour line extraction algorithm with selective thresholding according to line continuity

Abstract

AbstractThis paper describes a new contour line extraction algorithm which makes better contour line continuation and accelerates processing speed.When obtaining a contour line from an original gray‐scale image, the contour line extraction algorithm generally requires the following conditions: extracted contour lines representing a good feature of the original image; less invalid data such as noise; contour line width is one pixel thickness; and better contour connectedness. Many contour line extraction algorithms have been proposed. However, usually the user has employed the contour line extraction algorithm selecting by experience and a sixth sense. In the conventional method, differential operators are carried out on an original image with thresholding at a given value. Afterward, a thinning operation is carried out to obtain a one‐pixel thickness contour line. However, this process takes considerable computing time because the thinning process needs recursive processing.The new algorithm presented here carries out the process which performs the edge detection and thinning operation simultaneously eliminating the extra step. The process is effectively integrated in two ways: one is maximum point extraction in the differential image; and the other is the thresholding by introducing the selection of threshold values by using observance of the contour line connectedness in the differential image.As a result, the proposed algorithm is 10 times faster than the conventional methods in processing speed, and provides almost the same quality in contour line image.