Optical music notes recognition for printed piano music score sheet

Entertainment, Therapy and Education are the fields where music is always found in couple with homo-sapiens. Music is presented in various formats to us like aural, visual and one more - written form of music that is known very less to us. In a way music dominates our life. System discussed in this paper inputs music score written for piano music using modern staff notations as image. Segmentation is carried out using hierarchical decomposition using thresholding along with stave lines of score sheet. Segmented symbols are recognized through an established artificial neural network based on boosting approach. Recognized symbols are represented in an admissible way. System is capable enough of addressing very complex cases and validation is done over 53 songs available at various global music scores resources. Segmentation algorithms achieve accuracy of 99.12% and segmented symbols are recognized with prompt accuracy of 92.38% through the help of PCA and AdaBoost.