• 전기의세계
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• v.33 no.12
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• pp.726-734
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• 1984

본고에서는 아직도 연구지향의 성격을 띄고 있는 인공지능로보트의 시각시스템에 관해 기술하였고, 이들의 연구를 바탕으로 하여 needs에 답하는 형식인 응용지향인 산업용로보트의 시각시스템에 관해 언급하였다. 끝으로 필자의 연구실에서 발표한 인쇄악보의 인식에 관해 간단히 소개하였다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.113-116
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• 2001

This paper describes an analysis of the music as a time series and the fuzzy logic-based modeling of it. All music is made up of a finite number of musical notations known as the musical symbols, such as clefs, staff, tine signature, notes, rests, etc. . The musical score uses musical symbols to present various characteristics, such as rhythm, melody, chord, etc,. for interpreting the music. In this paper, it is possible to transform the beat and pitch in the musical into time series from the viewpoint of recognizing beat and pitch of sounding tone at each time. On the basis of the identified features of the musical score, a musical score is represented as a time series and then is constructed to fuzzy logic-based model for predicting them. Examples are presented to illustrate the validity of the proposed method.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.1
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• pp.19-26
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• 2019

In this paper, the classification performance of learning algorithms is compared for TAB digit recognition. The TAB digits that are segmented from TAB musical notes contain TAB lines and musical symbols. The labeling method and non-linear filter are designed and applied to extract fret digits only. The shift operation of the 4 directions is applied to generate more data. The selected models are Bayesian classifier, support vector machine, prototype based learning, multi-layer perceptron, and convolutional neural network. The result shows that the mean accuracy of the Bayesian classifier is about 85.0% while that of the others reaches more than 99.0%. In addition, the convolutional neural network outperforms the others in terms of generalization and the step of the data preprocessing.

• Journal of the Korean Institute of Telematics and Electronics
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• v.22 no.5
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• pp.10-16
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• 1985

In this paper, a computer vision system, which catches printed music score image using CCTV camera and microcomputer, and then recognizes the image and performs tar music with speaker, is discussed. Integral projection method is adopted for feature detection and recognition of the music score image. The range of recognition is con(ined to staffs, perpen-dicular lines and musical notes including chord notes among the various kinds of elements of music score. The practical recognition algorithm considering noises, the preprocessing processes getting rid of noises are also showed, and simple hardware system playing chord is made, In the results, good recognition ratio and performance are obtained.

• Proceedings of the Korean Society of Computer Information Conference
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• 2012.07a
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• pp.267-268
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• 2012

본 논문에서는 Google사의 Project glass를 이용한 피아노 연습 어플리케이션을 제안한다. 하지만 아직 이 기기는 발매되지 않았기 때문에 안드로이드 모바일에서 제작중이다. 사용자악보를 database로 간단하게 관리하고, OpenCV라이브러리를 통해 실제 피아노의 위치와 건반을 인식하고, 손가락의 위치 파악과 소리 인식을 통하여 서로 인식한 정보의 일치여부를 확인한다. 그리고 증강현실 기술을 이용하여 게임적인 요소를 추가시켜서 보다 쉽고, 재미있게 실제 피아노 연습을 할 수 있다. 본 논문에서는 기존에 피아노 연주 연습하는 방식에서 IT기술을 접목시켜서, 교육과 기술발전에 기여할 수 있음을 보인다. 그리고 앞으로 영상처리 기술이 널리 사용될 것으로 예상되어 미리 기술을 학습하는 효과도 있다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.7
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• pp.1098-1101
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• 2022

With the development of computer music notation programs, when drawing sheet music, it is often drawn using a computer. However, there are still many use of hand-written notations for educational purposes or to quickly draw sheet music such as listening and dictating. In previous studies, OMR focused on recognizing the printed music sheet made by music notation program. the result of handwritten OMR with camera is poor because different people have different writing methods, and lens distortion. In this study, as a pre-processing process for recognizing handwritten music sheet, we propose a method for recognizing a staff using linear regression and a method for recognizing a bar using CNN. F₁ scores of staff recognition and barline detection are 99.09% and 95.48%, respectively. This methodologies are expected to contribute to improving the accuracy of handwriting.

• The Journal of the Acoustical Society of Korea
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• v.15 no.1
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• pp.54-60
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• 1996

In most pattern recognition and image understanding applications, images are degraded by noise and other distortions. Therefore, it is more relevant to decide how similar two objects are rather than to decide whether the two are exactly the same. In this paper, we propose a method for recognizing degraded symbols using a distance measure between two graphs representing the symbols. a symbol is represented as a graph consisting of nodes and edges based on the run graph concept. The graph is then transformed into a reference model graph with production rule containing the embedding transform. The symbols are recognized by using the distance measure which is estimated by using the number of production rules used and the structural homomorphism between a transformed graph and a model graph. the proposed approach is applies to the recognition of non-note musical symbols and the result are given.

• The Journal of the Korea Contents Association
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• v.12 no.11
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• pp.9-19
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• 2012

Time-varying tempo of a song is one of the error sources for the identification of a note duration in automatic music recognition. This paper proposes an improved music transcription scheme equipped with the identification of note duration considering the time-varying tempo. In the proposed scheme the measures are found at first and the tempo, the playing time of each measure, is then estimated. The tempo is then used for resizing each IOI(Inter Onset Interval) length and considered to identify the accurate note duration, which increases the degree of correspondence to the music piece. In the experiment the proposed scheme found the accurate measure position for 14 monophonic children songs out of 16 ones recorded by men and women. Also, it achieved about 89.4% and 84.8% of the degree of matching to the original music piece for identification of note duration and pitch, respectively.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10b
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• pp.280-282
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• 1999

현존하는 클래식 음악에는 음악적, 심리적 작곡약속이 있다. 작곡약속을 악식(樂式) 혹은 음악형식(音樂形式)이라고 한다. 즉, 모든 악곡은 일정한 형식에 의하여 작곡된다. 이러한 이유로 악곡에서는 어떤 특징적인 note관계가 규칙적으로 반복해서 나타난다. 이러한 특성은 note간의 관계가 어떻게 변화하는가에 따라서, 악곡 전체에서 segment의 시작과 끝으로 인식되어진다. 본 논문에서는 악곡의 분석을 위해 실제 악보를 컴퓨터 데이터 형식으로 표현하기 위한 SFCM(Score Format for Computer Music)을 정의하여, 악곡의 note를 분석해서 각 소절(measure)별로 대표음 집합을 추출할 수 있도록 하였다. 각 소절의 대표음 집합을 이용해서, note의 변화에 따른 schematic을 생성한다 schematic 생성과 분석을 위해 note-schema의 규칙과 형식을 정의해 놓은 CNSDB(Changing-Note Schema DataBase)를 제안한다. 이러한 데이터 베이스를 이용하여 특징적인 규칙을 찾아내고, 적용해 악곡에서 segment를 나눌수 있다. 본 논문에서는 1700년대의 클래식 음악에서 특히 잘 나타나는 규칙을 적용해서 분석하였다.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.427-430
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• 1992

In this paper, we proposed an algorithm for the musical note recognition. Firstly, a given bit-mapped music score image is converted to a set of individual note pattern images via vertical projection. Then, the pitch of a note is determinal by comparison in the note-head position with the reference five-lines. Also, the length of a note is found via leader clustering with a set of normalized note patterns. Finally, a datafile to play the music is obtained using the pitch and length of musical notes. Experimental results with a simple musical score image show that the proposed scheme is performed well.