Abstract
A new method for dominant point detection is presented. This method can be classified as search corner detection using some significant measurement other than curvature category, and needs no input parameters. A new and normalized measurement is described to compute the estimated curvature and to detect dominant points, and a new algorithm is proposed to eliminate collinear points using an optimization procedure. The experimental results show that this method is efficient, effective, reduces the number of dominant points as compared to other proposed methods, and the obtained contours using this objective function are properly adjusted to the original contour.
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