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논문 기본 정보

자료유형
학술저널
저자정보
Cong Minh Dinh (Chonnam National University) Luu Ngoc Do (Chonnam National University) Hyung-Jeong Yang (Chonnam National University) Soo-Hyung Kim (Chonnam National University) Guee-Sang Lee (Chonnam National University)
저널정보
한국콘텐츠학회(IJOC) International JOURNAL OF CONTENTS International JOURNAL OF CONTENTS Vol.12 No.4
발행연도
2016.12
수록면
53 - 61 (9page)

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초록· 키워드

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Although extensively developed, optical music recognition systems have mostly focused on musical symbols (notes, rests, etc.), while disregarding the chord symbols. The process becomes difficult when the images are distorted or slurred, although this can be resolved using optical character recognition systems. Moreover, the appearance of outliers (lyrics, dynamics, etc.) increases the complexity of the chord recognition. Therefore, we propose a new approach addressing these issues. After binarization, un-distortion, and stave and lyric removal of a musical image, a rule-based method is applied to detect the potential regions of chord symbols. Next, a lexicon-driven approach is used to optimally and simultaneously separate and recognize characters. The score that is returned from the recognition process is used to detect the outliers. The effectiveness of our system is demonstrated through impressive accuracy of experimental results on two datasets having a variety of resolutions.

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ABSTRACT
1. INTRODUCTION
2. PROPOSED SYSTEM
3. EXPERIMENTS
4. CONCLUSION
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