A Rotation Invariant Rule-Based Thinning Algorithm for Character Recognition
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An Improved Parallel Thinning Algorithm
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This paper addresses an efficient parallel thinning algorithm based on weight-values. The weight-value of a black pixel is calculated by observing neighboring pixels, and it gives us an efficient way to decide whether the pixel is deleted or not. Owing to weight-values, the proposed algorithm uses only 33 templates. Furthermore, it examines only the elimination conditions corresponding the weight-value of boundary pixels, and all elimination conditions will not be searched as most other parallel iterative thinning algorithms. Thus, the execution time can be reduced much comparing to that of previous approaches. The weight-value also allows us to deal with typical troublesome patterns efficiently. Without smoothing before thinning, the algorithm produces robust thinned images even in the presence of two pixel-width noises. We obtain encouraging results from extensive experiments.