Presentation 1998/2/19
A Study of Feature Extraction by Information on Outline of Handwritten Chinese Characters : Peripheral Local Outline Vector & Peripheral Local Moment
Keitaro Hori, Koichi Nemoto, Akiyoshi Itoh,
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Abstract(in English) Peripheral direction contributivity (P-DC) is known as one of effective feature extraction methods for handwritten Chinese characters recognition. However, the feature vector of P-DC is not robust against any kinds of deformation. By using peripheral local outline vector (P-LOVE) which was proposed by us already, we show that the features extracted at the outline of characters are effective for the deformed characters. In addition, we propose a new feature extraction method, named peripheral local moment (P-LM), which is consists of second moment for local line segment of characters. Experimental results show that P-LOVE and P-LM achieve higher recognition rates than P-DC's either for ETL-9B.
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Keyword(in English) character recognition / feature extraction / direction contributivity / peripheral local outline vector / peripheral local moment / ETL-9B
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Committee PRMU
Conference Date 1998/2/19(1days)
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Registration To Pattern Recognition and Media Understanding (PRMU)
Language JPN
Title (in Japanese) (See Japanese page)
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Title (in English) A Study of Feature Extraction by Information on Outline of Handwritten Chinese Characters : Peripheral Local Outline Vector & Peripheral Local Moment
Sub Title (in English)
Keyword(1) character recognition
Keyword(2) feature extraction
Keyword(3) direction contributivity
Keyword(4) peripheral local outline vector
Keyword(5) peripheral local moment
Keyword(6) ETL-9B
1st Author's Name Keitaro Hori
1st Author's Affiliation NIHON Univ. Graduate School()
2nd Author's Name Koichi Nemoto
2nd Author's Affiliation NIHON Univ. Graduate School
3rd Author's Name Akiyoshi Itoh
3rd Author's Affiliation NIHON Univ. College of Sci. & Tech., Dep. of Electronic Engineering
Date 1998/2/19
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Volume (vol) vol.97
Number (no) 558
Page pp.pp.-
#Pages 8
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