| Project/Area Number |
63580032
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| Research Category |
Grant-in-Aid for General Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Research Field |
Informatics
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| Research Institution | CHUBU UNIVERSITY (1989)
Gifu Shotoku Gakuen Junior College (1988) |
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Principal Investigator |
YOSHIMURA Mitsu Chubu University, Associate Professor, 経営情報学部, 助教授 (60109311)
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| Co-Investigator(Kenkyū-buntansha) |
YOSHIMURA Isao Nagoya University, Associate Professor, 工学部, 助教授 (30010797)
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| Project Period (FY) |
1988 – 1989
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| Project Status |
Completed (Fiscal Year 1989)
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| Budget Amount *help |
¥2,000,000 (Direct Cost: ¥2,000,000)
Fiscal Year 1989: ¥300,000 (Direct Cost: ¥300,000)
Fiscal Year 1988: ¥1,700,000 (Direct Cost: ¥1,700,000)
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| Keywords | person identification / writer identification / arc pattern method / localized arc pattern method / off-line information / handwritten character / Japanese writings / modified Mahalanobis' distance / 筆跡 / 特徴抽出 / 相似パターンの頻度による筆者識別法 / ARCパターン変換法 |
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| Research Abstract |
1) We devised a new procedure called the 'Localized Arc Pattern Method' as an aid for person identification. It is implemented in a system where a person is identified through his writings. Any person who appears in front of this system is required to write a specified Japanese sentence in such a manner that any letter in the sentence is written one by one separately. Then each written character is transformed in a binary pattern and measured the frequencies of certain specified model patterns which are simplified forms of the arc patterns proposed by us in past. The person is identified with the Mahalanobis' distance based on these frequencies. In this system the idea of localization achieved to make the system small in the sense that the necessary memory and time is far smaller than other systems proposed in past, though it retains a high average correct identification rate.
2) To realize the above mentioned system as a personal computer system we programmed a software which can read written documents into a personal computer using an image scanner.
3) Since the individual personal tendency of distortion in writing plays an essential role in this system we tried to visualize this individuality through reconstruction of characters which well represent the personal tendencies of writings.
4) In the realized small scale personal identification system based on writings a menu with the following four parts appears: 1. Character data input part, 2. Feature extraction part, 3. Generation dictionary part, 4. Identification part. But the limited scale of the personal computer made the system unsatisfactory for us in the implementation because the MS-FORTRAN on MS-DOS can not afford go much memory as a system.
5) We submitted or are going to submit some papers in this study to related journals such as the PAMI of IEEE or the Pattern Recognition. We read some papers in IECIE conferences or the 9th ICPR.
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