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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 발행연도
- 2009.8
- 수록면
- 1,095 - 1,099 (5page)
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초록· 키워드
오류제보하기
For natural and intuitive interaction, research on acceleration-based interfaces to recognize handwriting is becoming popular. When recognizing handwriting, a problem exists in distinguishing between naturally similar letters and numbers. This problem severely affects the total recognition rate. To solve this problem, Cho et al. [4] used a two-stage recognizer, which separated confusing pairs from entire handwriting samples and then classified these during a second stage. In this paper, a feature extraction method to recognize similarly handwritten characters without using the two-stage procedure is investigated. As feature elements, temporal and statistical parameters from the accelerometer are calculated. Two feature extraction methods are proposed: creating vectors using these parameters, and remodeling each signal using these parameters. Dynamic Time Warping (DTW) is used to recognize these feature vectors. Results show a 3 dimensional feature vector is better at recognizing handwriting samples than a 2 dimensional vector, and the combination of acceleration and velocity is also better than other methods. From the overall results, a remodeled signalis acceptable in recognizing naturally similar handwritten characters.
목차
Abstract
1. INTRODUCTION
2. RESEARCH MOTIVATION
3. EXPERIMENTS
4. CONCLUSION
REFERENCES
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UCI(KEPA) : I410-ECN-0101-2014-569-000764028