Presentation | 2007-03-15 An Analytic Word Recognition Algorithm Using a Posteriori Probability : Normalization of the number of segmentation candidates Tomoyuki HAMAMURA, Takuma AKAGI, Bunpei IRIE, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Word recognition algorithms are classified into two major groups. One is an "analytic" approach of recognizing individual characters, while the other is a "holistic" approach dealing with an entire word image. In the former approach, we have proposed an evaluation function (Normalized a posteriori probability ratio) that has been derived from an a posteriori probability of a word in a lexicon in order to make it easy-to-compute. In this paper, we point out that an approximation error of this evaluation function be fairly large when an employed segmentation method generates many segments. Furthermore, improved derivation of the a posteriori probability is proposed, and a new evaluation function (enhanced a posteriori probability ratio) is derived, which is more precise without losing easy-to-compute feature. A result of an experiment using real images shows 9.1 % improvement on handwritten word recognition. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Word recognition / Analytic / Evaluation function / A posteriori probability / A posteriori probability ratio / Normalized a posteriori probability ratio / Enhanced a posteriori probability ratio |
Paper # | PRMU2006-238 |
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Conference Information | |
Committee | PRMU |
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Conference Date | 2007/3/8(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Pattern Recognition and Media Understanding (PRMU) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | An Analytic Word Recognition Algorithm Using a Posteriori Probability : Normalization of the number of segmentation candidates |
Sub Title (in English) | |
Keyword(1) | Word recognition |
Keyword(2) | Analytic |
Keyword(3) | Evaluation function |
Keyword(4) | A posteriori probability |
Keyword(5) | A posteriori probability ratio |
Keyword(6) | Normalized a posteriori probability ratio |
Keyword(7) | Enhanced a posteriori probability ratio |
1st Author's Name | Tomoyuki HAMAMURA |
1st Author's Affiliation | TOSHIBA Corp.() |
2nd Author's Name | Takuma AKAGI |
2nd Author's Affiliation | TOSHIBA Corp. |
3rd Author's Name | Bunpei IRIE |
3rd Author's Affiliation | TOSHIBA Corp. |
Date | 2007-03-15 |
Paper # | PRMU2006-238 |
Volume (vol) | vol.106 |
Number (no) | 605 |
Page | pp.pp.- |
#Pages | 6 |
Date of Issue |