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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2009.12
- 수록면
- 1,718 - 1,727 (10page)
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초록· 키워드
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Traditional character recognition systems usually aim at characters with simple variation. With the development of multimedia technology, printed characters may appear more diversely. Existing recognition technologies can't deal with Hangul recognition effectively in diverse environments. This paper presents a recognition system for multi-form Korean characters called RSMFK, which is based on the model of Hierarchical Temporal Memory (HTM). Our system can effectively recognize the printed Korean characters of different fonts, scales, rotation, noise and background. HTM is a model which simulates the neocortex of human brain to recognize and memorize intelligently. Experimental results show that RSMFK performs a good recognition rate of 97.8% on average, which is proved to be obviously improved over the conventional methods.
목차
ABSTRACT
1. INTRODUCTION
2. The HTM Theory and Characteristics of Hangul
3. RECOGNITION SYSTEM FOR MULTIFORM KOREAN CHARACTERS
4. EXPERIMENT
5. COMPARISON WITH OTHER RESEARCHES
6. CONCLUSION AND DISCUSSION
REFERENCES
참고문헌 (12)
참고문헌 신청
1. [학술지(정기간행물)] - S. Araokar / 2005 / Visual Character Recognition using Artificial Neural Networks / Computer Science - Neural and Evolutionary Computing
2. [학술대회논문] - K.J.Pyeoung / 1993 / Hangul Recognition on Multi-Transputer System [J] / IEEE Region 10 Conference on Communication, Control and Power Engineering : 1102 ~ 1105
3. [학술지(정기간행물)] - K. Kang / 2003 / Handwritten Hangul Character Recognition with Hierarchical Stochastic Character Representation [A] / IEEE Computer Society 1 : 212 ~ 216
4. [학술지(정기간행물)] - P. Lee / 1994 / A study on printed Hangul recognition with dynamic Jaso segmentation and neural network [J] / Journal of Korean Institute of Communication : 2133 ~ 2145
5. [학술지(정기간행물)] - J. koh / 1990 / Korean Character Recognition Using Neural Networks [J] / 3rd Symposium on the Frontiers of Massively Parallel Computation : 162 ~ 165
2. [학술대회논문] - K.J.Pyeoung / 1993 / Hangul Recognition on Multi-Transputer System [J] / IEEE Region 10 Conference on Communication, Control and Power Engineering : 1102 ~ 1105
3. [학술지(정기간행물)] - K. Kang / 2003 / Handwritten Hangul Character Recognition with Hierarchical Stochastic Character Representation [A] / IEEE Computer Society 1 : 212 ~ 216
4. [학술지(정기간행물)] - P. Lee / 1994 / A study on printed Hangul recognition with dynamic Jaso segmentation and neural network [J] / Journal of Korean Institute of Communication : 2133 ~ 2145
5. [학술지(정기간행물)] - J. koh / 1990 / Korean Character Recognition Using Neural Networks [J] / 3rd Symposium on the Frontiers of Massively Parallel Computation : 162 ~ 165
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