Article

Segmentation of connected handwritten numeral strings

Department of Computer Science, University of Sharjah, P.O. Box 27272, Sharjah, United Arab Emirates; Department of Computer Science, University of Calgary, 2500 University Dr. NW, Calgary, Alberta, Canada T1N 2N2
Pattern Recognition 01/2003; DOI:10.1016/S0031-3203(02)00097-3 pp.625-634
Source: DBLP

ABSTRACT 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.

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Keywords

algorithm
 
CEDAR CD-ROM
 
connected numerals
 
Experimental results
 
NIST Database 19
 
own collection
 
successful recognition rate