Part-based recognition of handwritten characters

Seiichi Uchida, Marcus Liwicki

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

17 Citations (Scopus)

Abstract

In the part-based recognition method proposed in this paper, a handwritten character image is represented by just a set of local parts. Then, each local part of the input pattern is recognized by a nearest-neighbor classifier. Finally, the category of the input pattern is determined by aggregating the local recognition results. This approach is opposed to conventional character recognition approaches which try to benefit from the global structure information as much as possible. Despite a pessimistic expectation, we have reached recognition rates much higher than 90% for a digit recognition task. In this paper we provide a detailed analysis in order to understand the results and find the merits of the local approach.

Original languageEnglish
Title of host publicationProceedings - 12th International Conference on Frontiers in Handwriting Recognition, ICFHR 2010
Pages545-550
Number of pages6
DOIs
Publication statusPublished - Dec 1 2010
Event12th International Conference on Frontiers in Handwriting Recognition, ICFHR 2010 - Kolkata, India
Duration: Nov 16 2010Nov 18 2010

Publication series

NameProceedings - 12th International Conference on Frontiers in Handwriting Recognition, ICFHR 2010

Other

Other12th International Conference on Frontiers in Handwriting Recognition, ICFHR 2010
CountryIndia
CityKolkata
Period11/16/1011/18/10

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

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  • Cite this

    Uchida, S., & Liwicki, M. (2010). Part-based recognition of handwritten characters. In Proceedings - 12th International Conference on Frontiers in Handwriting Recognition, ICFHR 2010 (pp. 545-550). [5693620] (Proceedings - 12th International Conference on Frontiers in Handwriting Recognition, ICFHR 2010). https://doi.org/10.1109/ICFHR.2010.90