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• W2592420005 abstract "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." @default.
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• W2592420005 date "2016-12-28" @default.
• W2592420005 modified "2023-09-24" @default.
• W2592420005 title "Improved Lexicon-driven based Chord Symbol Recognition in Musical Images" @default.
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• W2592420005 doi "https://doi.org/10.5392/ijoc.2016.12.4.053" @default.
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