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Proceedings Paper

Graph-rewriting approach to discrete relaxation: application to music recognition
Author(s): Hoda M. Fahmy; Dorothea Blostein
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Paper Abstract

In image analysis, low-level recognition of the primitives plays a very important role. Once the primitives of the image are recognized, depending on the application, many types of analyses can take place. It is likely that associated with each object or primitive is a set of possible interpretations, herein referred to as the label set. The low-level recognizer may associate a probability with each label in the label set. We can use the constraints of the application domain to reduce the ambiguity in the object's identity. This process is variously termed constraint satisfaction, labeling, or relaxation. In this paper, we focus on the discrete form of relaxation. Our contribution lies in the development of a graph-rewriting approach which does not assume the degree of localness is high. We apply our approach to the recognition of music notation, where non-local interactions between primitives must be used in order to reduce ambiguity in the identity of the primitives. We use graph-rewriting rules to express not only binary constraints, but also higher-order notational constraints.

Paper Details

Date Published: 23 March 1994
PDF: 12 pages
Proc. SPIE 2181, Document Recognition, (23 March 1994); doi: 10.1117/12.171116
Show Author Affiliations
Hoda M. Fahmy, Queen's Univ. (Canada)
Dorothea Blostein, Queen's Univ. (Canada)


Published in SPIE Proceedings Vol. 2181:
Document Recognition
Luc M. Vincent; Theo Pavlidis, Editor(s)

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