Music score analysis method and device based on feature rules

Abstract

The invention discloses a music score analysis method and device based on feature rules. Firstly, a camera is used for carrying out image collection on a paper music score, the area where the music score is located is detected in the collected image, and rotation correction is carried out on the music score image in the area. In the corrected music score image, the score lines and the symbols are separated according to the score line characteristics of the music score, and the pixel coordinates of the score lines and the symbols on the image are obtained at the same time. The separated symbols are classified according to symbol features and are divided into two types of symbols, namely symbols and descriptors, and correlation among the symbols, the descriptors and the symbols can be obtained according to pixel coordinates. The symbols can acquire tone and beat number information of the notes, and the descriptors can acquire music score information such as tone numbers, music score numbers, continuous tones, rising and falling tones and the like. The music information contained in the music score can be intelligently analyzed by integrating the symbols, the descriptors and the incidence relation between the symbols and the descriptors. The music score analysis method disclosed by the invention has the characteristic of high note recognition accuracy.

Description

technical field [0001] The invention belongs to the field of optical music image recognition, and specifically designs a musical score analysis method and device based on feature rules. Background technique [0002] Optical music image recognition is the development and application of computer technology in the field of music. It mainly uses image processing, pattern recognition, document image analysis and other related technologies to convert score images into common digital music formats. Optical music image recognition realizes the digitization of traditional music scores, and has broad application prospects in many fields such as computer music, computer-aided music teaching, and digital music libraries. [0003] In score analysis, the identification, classification and understanding of note objects are the main difficulties. The main method is to preprocess the image information acquired by the camera to obtain complete and accurate score information, and then analyze...

AI Technical Summary

Problems solved by technology

Most of the current score analysis algorithms are based on image recognition methods, which directly identify features. The disadvantage is that it is prone to misidentification and large deviations.

A small number of music score analysis algorithms will make logical judgments based on the connection between the music score and the context to increase the recognition accuracy. The shortcoming is that it cannot accurately apply some unique experiences and rules of musical notes

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