The improvement of producing skeletons that preserve the significant geometric features of patterns is of great importance. One of feasible approaches is to develop a method embedded in a known parallel algorithm to produce bias-reduced skeletons since a bias skeleton usually degrades the preservation of significant geometric features of patterns. From our observations, bias skeletons always appear in the junction of lines which form an angle less than or near equal to 90 degrees. In this paper, the hidden deletable pixel (HDP) which influences the speed of deleting the boundary pixels on a concave side is newly defined. Based on the comparable performance of our pseudo l-subcycle parallel thinning algorithm (CH), a reduced form of larger support (two L-pixel vectors, which is not the form of k x k support) operated by an intermediate vector analysis about the deleted pixels in each thinning iteration is developed for HDP detection to obtain bias-reduced skeletons, which can be purchased by a reasonable computation cost. HDP restoration and parallel implementation are further considered to formulate an improved algorithm (CYS), where the connectivity preservation is guaranteed by the use of CH's operators and HDP restoration. A set of synthetic images are used to quantify the skeleton from the geometry viewpoint and investigate the skeleton variations of using different (L)s. Based on the analyzing results, 3 less than or equal to L less than or equal to 9 are suggested for the current algorithm of CYS. CYS is evaluated in comparison with two small support algorithms (AFP3 and CR) and one larger support algorithm (VRCT) using the same patterns. Performances are reported by the number of iterations (NI), CPU time (TC), and number of unmatched pixels (N-unmatch for bias-reduced measure). Results show that on the measure of TC, CYS is approximately 2 to 3 times slower than the others, while on the measure of NI, the four algorithms have approximately identical performance. On the measure of N-unmatch, CYS is approximately 2 to 3 times less than the others. One-pixel boundary noise is also considered for exploring the noise immunity. The results suggest that the noise immunity of CYS and CH is identical and is better than that of AFP3. As a result, the better bias-reduced skeletons produced by CYS may be purchased by a reasonable computation cost. (C) 1998 Academic Press.
