NEW OPTICAL MUSIC RECOGNITION MODEL TO ENHANCE THE BUSINESS PROCESS OF DEVELOPING MUSIC

摘要

The optical music symbol recognition system still has many challenges. Most of issues focused on the recognition of the individual marks in the input concert documents. In this paper a new and efficient model for optical music recognition (OMR) is proposed. The music marks is recognized and played by the computer OMR system automatically. Stored files of music documents has been treated sequentially as inputs to the off-line recognition system. A new algorithm for staff-lines removing is proposed also. This new technique is applied on the thinned image (document) without affecting the marks. Features have been extracted from isolated marks and stored as a training data. A wave files has been stored for the same marks played by a guitarist as an example. Minimum distance classifier is used as a recognition approach. Proposed model improves the music information technology (MIT) and develops the music academies courses and music distance learning. That leads to enhance the business process of developing music and music scientists.