A COMPARISON OF SPLITTING METHODS FOR THE IDENTIFICATION OF CORNER-POINTS

The problem of detecting corner-points in two-dimensional image curves, using splitting methods is addressed. The question of interest is how to reduce computing time without sacrificing quality in corner-point positioning. Three algorithms are compared: the classical Iterative-End-Point algorithm; a modified, line search method; and our proposal, using incremental distance calculations. There is a problem with the line search approach, because the set of points it identifies may include spurious corner-points. The proposed algorithm, however, maintains the quality of, and is three times faster, than the classical algorithm.