Segmentation of connected handwritten numeral strings
A new approach to separating single touching handwritten digit strings is presented. The image of the connected numerals is normalized, preprocessed and then thinned before feature points are detected. Potential segmentation points are determined based on decision line that is estimated from the deepest/highest valley/hill in the image. The partitioning path is determined precisely and then the numerals are separated before restoration is applied. Experimental results on the NIST Database 19, CEDAR CD-ROM and our own collection of images show that our algorithm can get a successful recognition rate of 96%, which compares favorably with those reported in the literature. (C) 2002 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.
thinning feature points character segmentation unconstrained handwritten numerals