Presentation | 1995/9/28 Fast Handwritten Character Recognition with Large Scale Multi-templates Shuji SENDA, Michihiko MINOH, Katsuo IKEDA, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Recently, it has been reported that quadratic discriminant functions are effective in handwritten character recognition. However, the quadratic discriminant functions have problems that they can not deal with the distribution other than the normal one and that their parameters are difficult to be esti-mated. In this paper, we apply a non-parametric discrimination, k nearest neighbor rule, to handwritten character recognition, using a large scale multi-template dictionary and a linear discriminant function. In order to accelerate the recognition process, we propose to use a rough classifier that decides character candidates by thresholding normalized distances. In the experiment of 3036-category classification with ETL9B, 9 nearest neighbor classifier achieved a high recognition rate of 97.48%. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | rough classification / multi-template / handwritten character recognition / ETL9B |
Paper # | PRU95-116 |
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Committee | PRU |
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Conference Date | 1995/9/28(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Pattern Recognition and Understanding (PRU) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Fast Handwritten Character Recognition with Large Scale Multi-templates |
Sub Title (in English) | |
Keyword(1) | rough classification |
Keyword(2) | multi-template |
Keyword(3) | handwritten character recognition |
Keyword(4) | ETL9B |
1st Author's Name | Shuji SENDA |
1st Author's Affiliation | Kyoto University() |
2nd Author's Name | Michihiko MINOH |
2nd Author's Affiliation | Kyoto University |
3rd Author's Name | Katsuo IKEDA |
3rd Author's Affiliation | Kyoto University |
Date | 1995/9/28 |
Paper # | PRU95-116 |
Volume (vol) | vol.95 |
Number (no) | 278 |
Page | pp.pp.- |
#Pages | 6 |
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