By Topic

Computer recognition of hand-written characters using the distance transform

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $31
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Kovacs, Z.M. ; Bologna Univ., Italy ; Guerrieri, R.

A new statistical classifier for hand-written character recognition is presented. The system features a preprocessing phase for image normalisation and a distance transform applied to the normalised image, which converts a B/W picture into a grey scale image. A k-nearest-neighbour classifier follows, based on the distance transform and a suitable metric. The system has an accuracy of 98.96% when applied to the US Post Office zip code database at 0.98% error rate.

Published in:

Electronics Letters  (Volume:28 ,  Issue: 19 )