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Author Kozielski, M. ♦ Forster, J. ♦ Ney, H.
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2012
Language English
Subject Domain (in DDC) Technology ♦ Engineering & allied operations ♦ Other branches of engineering
Subject Keyword Hidden Markov models ♦ Databases ♦ Shape ♦ Image segmentation ♦ Vectors ♦ Handwriting recognition ♦ Error analysis ♦ IAM ♦ OCR ♦ handwriting ♦ moments ♦ normalization ♦ Rimes
Abstract In this paper, we extend the concept of moment-based normalization of images from digit recognition to the recognition of handwritten text. Image moments provide robust estimates for text characteristics such as size and position of words within an image. For handwriting recognition the normalization procedure is applied to image slices independently. Additionally, a novel moment-based algorithm for line-thickness normalization is presented. The proposed normalization methods are evaluated on the RIMES database of French handwriting and the IAM database of English handwriting. For RIMES we achieve an improvement from 16.7% word error rate to 13.4% and for IAM from 46.6% to 40.4%.
ISBN 9781467322621
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2012-09-18
Publisher Place Italy
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 296.78 kB
Page Count 6
Starting Page 256
Ending Page 261


Source: IEEE Xplore Digital Library