The distinctiveness of a curve in a parameterized neighborhood: extraction and applications

A new feature of curves pertaining to the acceptance/rejection decision in curve detection is proposed. The feature measures a curve's distinctiveness in its neighborhood, which is modeled by a one-parameter family of curves. A computational framework based on the Hough transform for extracting the distinctiveness feature is elaborated and examples of feature extractors for the circle and the ellipse are given. It is shown that the proposed feature can be extracted efficiently and is effective in separating signals from false positives. Experimental results with circle and ellipse testing that strongly support the efficiency and effectiveness claims are obtained. The results further demonstrate that the proposed feature exhibits good noise resiliency

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