A Covariance-matching-based Model for Musical Symbol Recognition

• 발행기관: 한국스마트미디어학회
• 저자명: Luu-Ngoc Do Hyung-Jeong Yang Soo-Hyung Kim Guee-Sang Lee Cong Minh Dinh
• 간행물 정보: 『스마트미디어저널』Vol7, No.2, 23~33쪽, 전체 11쪽
• 주제분류: 공학 > 컴퓨터학
• 파일형태: PDF
• 발행일자: 2018.06.30

영문 초록

A musical sheet is read by optical music recognition (OMR) systems that automatically recognize and reconstruct the read data to convert them into a machine-readable format such as XML so that the music can be played. This process, however, is very challenging due to the large variety of musical styles, symbol notation, and other distortions. In this paper, we present a model for the recognition of musical symbols through the use of a mobile application, whereby a camera is used to capture the input image; therefore, additional difficulties arise due to variations of the illumination and distortions. For our proposed model, we first generate a line adjacency graph (LAG) to remove the staff lines and to perform primitive detection. After symbol segmentation using the primitive information, we use a covariance-matching method to estimate the similarity between every symbol and pre-defined templates. This method generates the three hypotheses with the highest scores for likelihood measurement. We also add a global consistency (time measurements) to verify the three hypotheses in accordance with the structure of the musical sheets; one of the three hypotheses is chosen through a final decision. The results of the experiment show that our proposed method leads to promising results.

목차

I. INTRODUCTION

II. RELATED WORK

III. PROPOSED SYSTEM

IV.Experimental Results

V. Conclusion

키워드

musical-symbol recognition covariance-matching image processing pattern recognition musical rules