A. Carmona-Poyato, N. L. Fernández-Garca, R. MedinaCarnicer and F. J. Madrid-Cuevas, “Dominant Point Detection: A New Proposal,” Image and Vision Computing, Vol. 23, No. 13, 2005, pp. 1226-1236. doi:10.1016/j.imavis.2005.07.025

has been cited by the following article:

• TITLE: On the Detection of Visual Features from Digital Curves Using a Metaheuristic Approach

  AUTHORS: Cecilia Di Ruberto

  KEYWORDS: Digital Curve; Dominant Point; Polygonal Approximation; Ant Colony Optimization

  JOURNAL NAME: Applied Mathematics, Vol.3 No.11A, November 27, 2012

  ABSTRACT: In computational shape analysis a crucial step consists in extracting meaningful features from digital curves. Dominant points are those points with curvature extreme on the curve that can suitably describe the curve both for visual perception and for recognition. Many approaches have been developed for detecting dominant points. In this paper we present a novel method that combines the dominant point detection and the ant colony optimization search. The method is inspired by the ant colony search (ACS) suggested by Yin in [1] but it results in a much more efficient and effective approximation algorithm. The excellent results have been compared both to works using an optimal search approach and to works based on exact approximation strategy.