• Journal of Internet Computing and Services
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• v.16 no.1
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• pp.29-37
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• 2015

In this paper, we propose a robust pre-processing module for camera-based Optical Music Score Recognition (OMR) on mobile device. The captured images likely suffer for recognition from many distortions such as illumination, blur, low resolution, etc. Especially, the complex background music sheets recognition are difficult. Through any symbol recognition system, the staff line height and staff line space are used many times and have a big impact on recognition module. A robust and accurate staff line height and staff line space are essential. Some staff line height and staff line space are proposed for binary image. But in case of complex background music sheet image, the binarization results from common binarization algorithm are not satisfactory. It can cause incorrect staff line height and staff line space estimation. We propose a robust staff line height and staff line space estimation by using run-length encoding technique on edge image. Proposed method is composed of two steps, first step, we conducted the staff line height and staff line space estimation based on edge image using by Sobel operator on image blocks. Each column of edge image is encoded by run-length encoding algorithm Second step, we detect the staff line using by Stable Path algorithm and removal the staff line using by adaptive Line Track Height algorithm which is to track the staff lines positions. The result has shown that robust and accurate estimation is possible even in complex background cases.

• The Journal of Korean Association of Computer Education
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• v.8 no.5
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• pp.109-118
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• 2005

In this paper, we present a music retrieval system that compares the geometric structure of a melody specified by a user with those in a music database. The system finds matches between a query melody and melodies in the database by analyzing both structural and contextual features. The retrieval method is based on the geometric hashing algorithm which consists of two steps; the preprocessing step and the recognition step. During the preprocessing step, we divide a melody into several fragments and analyze the pitch and duration of each note of the fragments to find a structural feature. To find a contextual feature, we find a main chord for each fragment. During the recognition step, we divide the query melody specified by a user into several fragments and search through all fragments in the database that are structurally and contextually similar to the melody. A vote is cast for each of the fragments and the music whose total votes are the maximum is the music that contains a matching melody against the query melody. Using our approach, we can find similar melodies in a music database quickly. We can also apply the method to detect plagiarism in music.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.19 no.3
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• pp.294-303
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• 2008

ISAR(Inverse Synthetic Aperture Radar) images represent the 2-D(two-dimensional) spatial distribution of RCS (Radar Cross Section) of an object, and they can be applied to the problem of target identification. A traditional approach to ISAR imaging is to use a 2-D IFFT(Inverse Fast Fourier Transform). However, the 2-D IFFT results in low resolution ISAR images especially when the measured frequency bandwidth and angular region are limited. In order to improve the resolution capability of the Fourier transform, various high-resolution spectral estimation approaches have been applied to obtain ISAR images, such as AR(Auto Regressive), MUSIC(Multiple Signal Classification) or Modified MUSIC algorithms. In this study, these high-resolution spectral estimators as well as 2-D IFFT approach are combined with a recently developed ISAR image classification algorithm, and their performances are carefully analyzed and compared in the framework of radar target recognition.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.69-77
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• 2021

This paper deals with the development of an application that converts the PDF music score entered by the user into a MIDI file of the chord the user wants. This application converts the PDF file into a PNG file for chord conversion when the user enters the PDF music score file and the chord which the user wants to change. After recognizing the melody of sheet music through image processing algorithm and recognizing the tempo of sheet music notes through deep learning, then the MIDI file of chord for existing sheet music is produced. The OpenCV algorithm and deep learning can recognize minim note, quarter note, eighth note, semi-quaver note, half rest, eighth rest, quarter rest, semi-quaver rest, successive notes and chord notes. The experiment shows that the note recognition rate of the music score was 100% and the tempo recognition rate was 90% or more.

• Journal of Korea Multimedia Society
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• v.21 no.1
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• pp.69-76
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• 2018

Augmented Reality (AR) technology has rapidly been applied to various application areas including e-learning and e-education. Focusing on the design and development of android tablet application, this study targeted to develop infant music education using AR technology. We used a tablet instead of personal computer because it is more easily accessible and more convenient. Our system allows infant users to play with teaching aids like blocks or puzzles to mimic musical play like game. The user sets the puzzle piece on the playground in front of the tablet and presses the play button. Then, the system extracts a region of interest among the images acquired by internal camera and separates the foreground image from the background image. The block recognition software analyzes, recognizes and shows the result using AR technology. In order to have reasonably working recognition ratio, we did experiments with more than 5,000 frames of actual playing scenarios. We found that the recognition rate can be secured up to 95%, when the threshold values are selected well using various condition parameters.

• Proceedings of the KSPS conference
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• 2005.11a
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• pp.147-150
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• 2005

The performance of speech recognition in car environment is severely degraded when there is music or news coming from a radio or a CD player. Since reference signals are available from the audio unit in the car, it is possible to remove them with an adaptive filter. In this paper, we present experimental results of speech recognition in car environment using the echo canceller. For this, we generate test speech signals by adding music or news to the car noisy speech from Aurora2 DB. The HTK-based continuous HMT system is constructed for a recognition system. In addition, the MMSE-STSA method is used to the output of the echo canceller to remove the residual noise more.

• The Journal of the Korea Contents Association
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• v.8 no.6
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• pp.16-25
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• 2008

Today, mobile phone is a necessity of modern life. For that reason, we suggest a particular system of a mobile phone which take a picture of music score image and automatically play it without any technical knowledges about the music score information. This experiment makes midi, acknowleging separate symbols via preprocessing to music score image taken. This paper utilizes 11 sorts of the score image taken by a mobile phone camera for this experiment. Through this method we suggest, as much as 98% on average takes place, which is very high recognizing ratio. Also, as we introduce this system in a mobile phone by porting, it takes 8.63 seconds on average to create midi following input of images.

• International Journal of Contents
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• v.12 no.4
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• pp.53-61
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• 2016

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.

• Journal of the Korean Society of Costume
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• v.51 no.5
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• pp.61-75
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• 2001

This study was intended to observe strategic fashion-presentation in Music stars according to the change of the star system in the Korean popular musics. The Korean Music stars since 1990s have been made, fabricated and have excessively depended on the demand of the teenagers. Therefore their distinctive fashion-presentation is considered as more important element than those of the past. Consequently. the characteristics of the fashion-presentation in the Korean Music star these days are as follows : First. Music stars shows fashion-presentation that has a consistent fashion theme. That is one of the key success factor to raise the recognition of star singer. Second. Music star produces fashion images which reflects identity and of subculture. Those appearance have won wild popularity of the Peeps 1990's new generation. Third. although there is no change music genre and emotion. through merely renovation of their fashion image, Music star got diversity and originality of the characteristics of contemporary cultural goods. Fourth. In case of famous dance groups, in the past they maintained a singular atmosphere as a group, but in 1990'Music star group each members of the group have individually fashion-presentation. So, they can get more fans. Fifth, Music singers borrow or duplicate fashion-presentation from each others. Such as similar fashion-presentation guarantees support of the same fans.

• 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.