NATURAL SKELETONIZATION: NEW APPROACH FOR THE SKELETONIZATION OF HANDWRITTEN CHARACTERS

Abstract

In this paper we propose a new algorithm for the skeletonization of handwritten characters. Unlike traditional skeletonization algorithms that relay only on the configuration of a binary image pixel in deciding whether it is deletable or not, Natural Skeletonization (NS) integrates the gray-level information in this process. The underlying principle here, which stems from the elongated properties of the handwritten characters, is that medial pixels of a handwritten stroke are "naturally" darker than its side pixels. NS consists of three steps: (1) the decomposition step; (2) the thinning step; (3) the reconstruction step. The integration of gray-level information is facilitated by the iterative binarization at equally spaced thresholds, which highlights positional differences between the medial and side pixels of a stroke. The advantage of our approach over existing methods is demonstrated by its ability to prevent the "flooding water" and to prevent the boundary noise from developing extraneous branches. One important aspect of the approach is that it relaxes the skeletonization's dependence on the quality and shape of initial binary pattern. The experimental results indicate that the proposed algorithm substantially improves the skeletonization quality compared to experiments with traditional skeletonization methods.