Abstract
Handwriting recognition is now a standard feature in many hand-held computers. In most systems, recognition is currently limited to recognition of handwritten text and graphics. Ilowever, there is a need to extend recognition to multidimensional domains that are traditionally difficult to input with a keyboard on a desktop computer. In this paper, we address the problem of recognizing multidimensional objects by introducing a new class of grammars that we call constrained attribute grammars. In a constrained attribute grammar, semantic information is captured by attributes, while spatial relationships arc capture by constraints on the attribute values. In addition, the concepts of keyword and relevance of a keyword are considered to reduce the computational complexity of parsing such grammars. A computationally efficient parsing algorithm based on these concepts is also presented.
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© 1998 Springer-Verlag Berlin Heidelberg
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Pagallo, G.M. (1998). Constrained attribute grammars for recognition of multi-dimensional objects. In: Amin, A., Dori, D., Pudil, P., Freeman, H. (eds) Advances in Pattern Recognition. SSPR /SPR 1998. Lecture Notes in Computer Science, vol 1451. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0033254
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DOI: https://doi.org/10.1007/BFb0033254
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