Interpreting music manuscripts: A logic-based, object-oriented approach

  • W. Brent Seales
  • Arcot Rajasekar
Session IA1C — Document Processing & Character Recognition
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1024)


This paper presents a complete framework for recognizing classes of machine-printed musical manuscripts. Our framework is designed around the decomposition of a manuscript into objects such as staves and bars which are processed with a knowledge base module that encodes rules in Prolog. Object decomposition focuses the recognition problem, and the rule base provides a powerful and flexible way to encode the rules of a particular manuscript class. Our rule-base registers notes and stems, eliminates false-positives and correctly labels notes according to their position on the staff. We present results that show 99% accuracy at detecting note-heads and 95% accuracy in finding stems.


Musical Notation Staff Line Symbol Detection Symbol Recognition Musical Symbol 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • W. Brent Seales
    • 1
  • Arcot Rajasekar
    • 1
  1. 1.Computer Science DepartmentUniversity of KentuckyLexingtonUSA

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