Segmentation of handwritten digits using contour features

A new method of separating touching unconstrained handwritten digits is proposed. A binary image containing a string of touching digits is scanned to give contour chains. The chains are analyzed and subdivided into four kinds of regions: valleys, mountains, holes, and open regions. Individual points of interest in the outer contour are then identified, e.g., points of high curvature. The separating path is assumed to pass between some pair of these significant contour points (SCPs). Nine features of the SCPs are measured and are used to sort the list of all possible pairings of SCPs. Preliminary results show that the correct cut is sorted within the first three choices in 89% of tests