Many algorithms for vectorization by thinning have been devised and applied to a great variety of pictures and drawings for data compression, pattern recognition and raster-to-vector conversion. But parallel thinning algorithms which generate one-pixel-wide skeletons can have difficulty preserving the connectivity of an image. In this paper, we propose a 2-subiteration parallel thinning algorithm with template matching (PTA2T) which preserves image connectivity, produces thinner results, maintains very fast speed and generates one-pixel-wide skeletons.

In this paper, a generic approach for the analysis and design of parallel thinning algorithms is presented. The procedures for designing 4-subcycle/iteration, 2-subcycle/iteration, and 1-subcycle/iteration thinning algorithms are developed. The experimental results show that these thinning algorithms designed by proposed approach preserve image connectivity, produce thinner results, and obtain faster speed than many existing key thinning algorithms. As an example, a 1-subcycle/iteration algorithm and its experimental results were illustrated, which is in general about two times faster than others in the literature.

A perfectly parallel thinning algorithm (PPTA) is proposed. It can generate perfect skeletons, which consist of end points, break points, and hole points only. Experimental results show that the proposed PPTA can also preserve image connectivity, produce thinner skeletons, and is faster than many existing thinning algorithms. For example, it is twice as fast as one of the fastest parallel thinning algorithm by Holt, Stewart, Clint and Perrorte.

This paper deals with analyzing and comparing several key thinning algorithms in terms of various different methodologies. From these analyses and comparisons, a new sequential model thinning algorithm using heuristic, hybrid methods is presented. It intends to produce, based on past experience, thinned skeletons of thickness one from input patterns, keep connectivity, and eliminate unnecessary pixels. Several illustrative examples on various patterns were tested and the results compared. The parallel model thinning algorithm is still open.

Uses a combinatorial approach to analyse the differences of thinning algorithms among iteration and sub-iteration, thinning by coordinate and by edges of patterns. The authors also propose a serial model thinning algorithm in which the skeletons only consist of three types of points: connected points, end-points, and hole-points.>

A fast serial and parallel algorithm for thinning digital patterns is presented. The processing speed is faster than previous algorithms in that it reads pixels along the edge of the input pattern rather than all pixels in each iteration. Using this algorithm, an experiment is conducted and the patterns such as 'X', 'H', 'A', 'moving body', and 'leaf' are tested. The results show that this algorithm is faster, structure-preserving, and more flexible in that it can be done either sequentially or in parallel.>

An approach to thinning is presented that deletes pixels without using iterative transformations. It consists of four steps: computing an addition matrix, which assigns maximal values to the pixels on the medial axis; computing a comparative matrix; deleting the nonmaximum pixels; and deleting the endpoints. Experimental results show that this algorithm makes the skeleton closer to the medial axis and makes it more convenient to reconstruct the original pattern.>

A parallel thinning algorithm of C.M. Holt et al. (1987) is compared with an algorithm of D. Rutovitz (1966) and one by T.Y. Zhang and C.Y. Suen (1984). Analyses and experiments show that the Holt algorithm is similar to the Rutovitz algorithm. A heuristic modification to Rutovitz' algorithm is also proposed and the modified algorithm is faster than Holt's algorithm.