A system for scanning and segmenting cursively handwritten words into basic strokes

Abstract

This paper presents a segmentation method that partly mimics the cognitive-behavioral process used by human subjects to recover motor-temporal information from the image of a handwritten word. The approach does not exploit any thinning procedure, but rather a different typology of information is manipulated concerning the curvature of the word contour. Starting from the maximum curvature points roughly corresponding to the beginning of a stroke, the algorithm scans the word, following the natural course of the line and attempts to repeat the same movement as executed by the writer during the generation of the word. At each maximum curvature point, the line is segmented and reconstructed by a smooth interpolation of the most interior points belonging to the line just covered. At the end of the scanning process, a temporal sequence of motor strokes is obtained which plausibly composes the original intended movement.