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A gabor filter-based method for recognizing handwritten numerals

✍ Scribed by Yoshihiko Hamamoto; Shunji Uchimura; Masanori Watanabe; Tetsuya Yasuda; Yoshihiro Mitani; Shingo Tomita


Publisher
Elsevier Science
Year
1998
Tongue
English
Weight
465 KB
Volume
31
Category
Article
ISSN
0031-3203

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✦ Synopsis


We study a Gabor-filter-based method for handwritten numeral character recognition. The Gabor filter is based on a multi-channel filtering theory for processing visual information in the early stages of the human visual systems. The performance of the Gabor-filter-based method is demonstrated on the ETL-1 database. Experimental results show that the artificial neural-network classifier achieved the error rate of 2.34% for a test set of 7000 characters. Therefore, the Gabor-filter-based method should be considered in recognition of handwritten numeric characters.


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