A High Accurate Vision Algorithm on Measuring Arbitrary Contour

In order to measure the error of arbitrary contours, a high accurate visual algorithm is proposed. Firstly, a subpixel edge extraction algorithm based on local grayscale fitting is used to extract subpixel contours. And then we use the coarse-to-fine matching strategy, which uses the shape context feature of contours to perform coarse matching, and then based on iterative closest points to complete fine matching step. Finally, the neighborhood algorithm is proposed to calculate the contour error. Experiments show that the accuracy of this algorithm can reach 0.5 pixel, and this algorithm can apply to error measurement of any shape of contours.

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