Musical note recognition using Minimum Spanning Tree Algorithm

Autor: Rosda Ayuni, Yoppy Sazaki, S. Kom
Rok vydání: 2014
Předmět:
Zdroj: 2014 8th International Conference on Telecommunication Systems Services and Applications (TSSA).
DOI: 10.1109/tssa.2014.7065919
Popis: 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.
Databáze: OpenAIRE