• DocumentCode
    3580904
  • Title

    Musical note recognition using Minimum Spanning Tree Algorithm

  • Author

    Sazaki, Yoppy ; Ayuni, Rosda ; Kom, S.

  • Author_Institution
    Fac. of Comput. Sci., Sriwijaya Univ., Palembang, Indonesia
  • fYear
    2014
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Musical Notes are notes which is placed in staff. This research was developed a musical note recognition software using Minimum Spanning Tree Algorithm. This software was developed to help beginner in learning music especially in recognizing musical notes. The input for this software was musical notes image and the output were information of musical note which is name of musical note and beat´s length sound of recognized musical note. There were four pre-processing involved in this research namely Sobel edge detection, binarization, segmentation and scaling then the result from pre-processing was used in training process. Accuracy of musical note recognition using this algorithm reached 97.9 per cent out of 97 trained data and 97.4 per cent out of 40 tested data.
  • Keywords
    computer aided instruction; edge detection; image segmentation; music; trees (mathematics); Sobel edge detection; beat length sound; image binarization; image scaling; image segmentation; minimum spanning tree algorithm; music learning; musical note information; musical note recognition software; musical notes image; staff; Image recognition; Neural networks; Silicon; Software; Minimum Spanning Tree Algorithm; Musical Note; Musical Note Recognition; Sound;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Telecommunication Systems Services and Applications (TSSA), 2014 8th International Conference on
  • Type

    conf

  • DOI
    10.1109/TSSA.2014.7065919
  • Filename
    7065919