Nonuniform slant correction using dynamic programming

Seiichi Uchida, Eiji Taira, Hiroaki Sakoe

Research output: Chapter in Book/Report/Conference proceedingConference contribution

21 Citations (Scopus)

Abstract

Slant correction is an indispensable technique for handwritten word recognition systems. Conventional slant correction techniques estimate the average slant angle of component characters and then correct the slant uniformly. Thus these conventional techniques will perform successfully under the assumption that each word is written with a constant slant. However, it is more widely acceptable assumption that the slant angle fluctuates during writing a word. In this paper, a nonuniform slant correction technique is presented where the slant correction problem is formulated as an optimal estimaiton problem of local slant angles at all horizontal positions. The optimal estimation is governed by a criterion function and several constraints for the global and local validity of the local angles. The optimal local slant angles which maximize the criterion satisfying the constraints are searched for efficiently by a dynamic programming based algrithm. Experimental results show the advantageous characteristics of the present technique over the uniform slant correction techniques.

Original languageEnglish
Title of host publicationProceedings - 6th International Conference on Document Analysis and Recognition, ICDAR 2001
PublisherIEEE Computer Society
Pages434-438
Number of pages5
ISBN (Electronic)0769512631, 0769512631, 0769512631
DOIs
Publication statusPublished - Jan 1 2001
Event6th International Conference on Document Analysis and Recognition, ICDAR 2001 - Seattle, United States
Duration: Sep 10 2001Sep 13 2001

Publication series

NameProceedings of the International Conference on Document Analysis and Recognition, ICDAR
Volume2001-January
ISSN (Print)1520-5363

Other

Other6th International Conference on Document Analysis and Recognition, ICDAR 2001
CountryUnited States
CitySeattle
Period9/10/019/13/01

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

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