Abstract

The problem of critical points detection is important not only in the field of cartography but also in pattern recognition, image processing, computer vision, and artificial intelligence. In this paper, a new algorithm for critical points detection in raster data is given. The algorithm is based on finding the zero-crossings of the convoluted values of the second derivative of the Gaussian with the signal derived from the raster data. In addition, the results of the critical points detected by this algorithm are compared with those selected by humans. Moreover, the importance and usefulness of critical points detection in digital curves is outlined.

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