Edge detection in machine vision using a simple L1 norm template matching algorithm

Abstract Template matching based on the sum of absolute errors (the L 1 norm) is an effective means of edge detection in certain controlled imaging environments where the form of the edges to be detected is known. The algorithm employs a 1-D edge profile as the template. Edges are detected by computing the L 1 norm of an error vector obtained by subtracting an edge template from the image data. This paper evaluates the performance of the L 1 norm template matching algorithm and draws comparisons to classical correlation matching. The L 1 norm template matching algorithm has potential for integrated circuit and printed circuit board inspection, and other inspection applications where the lighting and view aspect can be controlled.

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