Presentation | 2008-03-13 Handwritten Character Distinction Inspired by Human Vision System Junpei KOYAMA, Masahiro KATO, Akira HIROSE, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | We deal with distinction between handwritten and machine-printed characters in document images. Current distinction techniques need extraction of characters and text lines from document images. However, the extraction is difficult if document images have handwritten characters. To solve the problem, we propose a distinction method inspired by human vision system. We transform every local region in document images into frequency domain data, and extract feature values which include fluctuations caused by handwriting. For the distinction, we employ a multilayer perceptron which learns the feature values. Experimental results show that our method doesn't need to locate characters or text lines. In addition, we analyze condition for the distinction experimentally. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Distinction between handwritten and machine-printed characters / Human vision system / Two dimensional Fourier transform / Power spectrum / Multilayer perceptron |
Paper # | NC2007-151 |
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Committee | NC |
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Conference Date | 2008/3/5(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Neurocomputing (NC) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Handwritten Character Distinction Inspired by Human Vision System |
Sub Title (in English) | |
Keyword(1) | Distinction between handwritten and machine-printed characters |
Keyword(2) | Human vision system |
Keyword(3) | Two dimensional Fourier transform |
Keyword(4) | Power spectrum |
Keyword(5) | Multilayer perceptron |
1st Author's Name | Junpei KOYAMA |
1st Author's Affiliation | The University of Tokyo() |
2nd Author's Name | Masahiro KATO |
2nd Author's Affiliation | Fuji Xerox Co., Ltd. |
3rd Author's Name | Akira HIROSE |
3rd Author's Affiliation | The University of Tokyo |
Date | 2008-03-13 |
Paper # | NC2007-151 |
Volume (vol) | vol.107 |
Number (no) | 542 |
Page | pp.pp.- |
#Pages | 6 |
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