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Decision Trees for Fast Thinning Algorithms

We propose a new efficient approach for neighborhood exploration, optimized with decision tables and decision trees, suitable for local algorithms in image processing. In this work, it is employed to speed up two widely used thinning techniques. The performance gain is shown over a large freely available dataset of scanned document images.