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  1. International Journal of Document Analysis and Recognition (IJDAR)
  2. International Journal of Document Analysis and Recognition (IJDAR) : Volume 20
  3. International Journal of Document Analysis and Recognition (IJDAR) : Volume 20, Issue 2, June 2017
  4. Online recognition of handwritten music symbols
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International Journal of Document Analysis and Recognition (IJDAR) : Volume 20
International Journal of Document Analysis and Recognition (IJDAR) : Volume 20, Issue 2, June 2017
Online recognition of handwritten music symbols
Eyes Wide Open: an interactive learning method for the design of rule-based systems
Unsupervised refinement of color and stroke features for text binarization
Online flowchart understanding by combining max-margin Markov random field with grammatical analysis
International Journal of Document Analysis and Recognition (IJDAR) : Volume 19
International Journal of Document Analysis and Recognition (IJDAR) : Volume 18
International Journal of Document Analysis and Recognition (IJDAR) : Volume 17
International Journal of Document Analysis and Recognition (IJDAR) : Volume 16
International Journal of Document Analysis and Recognition (IJDAR) : Volume 15
International Journal of Document Analysis and Recognition (IJDAR) : Volume 14
International Journal of Document Analysis and Recognition (IJDAR) : Volume 13
International Journal of Document Analysis and Recognition (IJDAR) : Volume 12
International Journal of Document Analysis and Recognition (IJDAR) : Volume 11
International Journal of Document Analysis and Recognition (IJDAR) : Volume 10
International Journal of Document Analysis and Recognition (IJDAR) : Volume 9
International Journal of Document Analysis and Recognition (IJDAR) : Volume 8
International Journal of Document Analysis and Recognition (IJDAR) : Volume 7
International Journal of Document Analysis and Recognition (IJDAR) : Volume 6
International Journal of Document Analysis and Recognition (IJDAR) : Volume 5
International Journal of Document Analysis and Recognition (IJDAR) : Volume 4
International Journal of Document Analysis and Recognition (IJDAR) : Volume 3
International Journal of Document Analysis and Recognition (IJDAR) : Volume 2
International Journal of Document Analysis and Recognition (IJDAR) : Volume 1

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Online recognition of handwritten music symbols

Content Provider Springer Nature Link
Author Oh, Jiyong Son, Sung Joon Lee, Sangkuk Kwon, Ji Won Kwak, jun
Copyright Year 2017
Abstract In this paper, we propose an effective online method to recognize handwritten music symbols. Based on the fact that most music symbols can be regarded as combinations of several basic strokes, the proposed method first classifies all the strokes comprising an input symbol and then recognizes the symbol based on the results of stroke classification. For stroke classification, we propose to use three types of features, which are the size information, the histogram of directional movement angles, and the histogram of undirected movement angles. When combining classified strokes into a music symbol, we utilize their sizes and spatial relation together with their combination. The proposed method is evaluated using two datasets including HOMUS, one of the largest music symbol datasets. As a result, it achieves a significant improvements of about 10% in recognition rates compared to the state-of-the-art method for the datasets. This shows the superiority of the proposed method in online handwritten music symbol recognition.
Starting Page 79
Ending Page 89
Page Count 11
File Format PDF
ISSN 14332833
Journal International Journal of Document Analysis and Recognition (IJDAR)
Volume Number 20
Issue Number 2
e-ISSN 14332825
Language English
Publisher Springer Berlin Heidelberg
Publisher Date 2017-02-15
Publisher Place Berlin, Heidelberg
Access Restriction One Nation One Subscription (ONOS)
Subject Keyword Music symbol recognition Online handwritten symbol recognition Histogram of directional movement angles Histogram of undirected movement angles Spatial relation Image Processing and Computer Vision Pattern Recognition
Content Type Text
Resource Type Article
Subject Computer Science Applications Computer Vision and Pattern Recognition Software
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