Thinning algorithms often cause stroke distortions at the crosses or intersections of strokes, which lead to bad results in pattern recognition tasks. In order to overcome these drawbacks, this paper proposes a parallel thinning algorithm based on stroke continuity detection. In the algorithm, before it uses the conditions of parallel algorithms to delete a boundary point, it first detects whether the boundary point is a reserved point to keep stroke’s continuity or not. Consequently, it can produce a skeleton with good symmetry, control the large deformation at the cross or intersection of strokes, and make a better skeleton more quickly. Moreover, it is practically immune to noise.
['Jianwei Dong', 'Yanmei Chen', 'Zhijing Yang', 'Bingo Wing-Kuen Ling']
A parallel thinning algorithm based on stroke continuity detection