Title :
Attribute grammar for shape recognition and its VLSI implementation
Author :
Cheng, H.D. ; Cheng, X.
Author_Institution :
Dept. of Comput. Sci., Utah State Univ., Logan, UT, USA
fDate :
30 Aug-3 Sep 1992
Abstract :
Shape recognition has wide applications in many fields. An attribute grammar approach to shape recognition combines both advantages of syntactic and statistical methods and makes shape recognition more accurate and efficient. However, the time complexity of a sequential shape recognition algorithm using attribute grammar is O(n3) where n is the length of an input string. The paper presents a parallel shape recognition algorithm and its implementation on a fixed-size VLSI architecture. The proposed algorithm has time complexity O(n3/k2). Experiments have also been conducted to verify the performance of the proposed algorithm. The proposed algorithm and architecture could be very useful for image processing, pattern recognition and related areas
Keywords :
VLSI; computational complexity; computer vision; grammars; parallel algorithms; pattern recognition; attribute grammar; computer vision; computerised pattern recognition; fixed-size VLSI architecture; image processing; parallel algorithm; pattern recognition; shape recognition; time complexity; Application software; Computer science; Data mining; Image processing; Image recognition; Partitioning algorithms; Pattern analysis; Pattern recognition; Shape; Very large scale integration;
Conference_Titel :
Pattern Recognition, 1992. Vol.I. Conference A: Computer Vision and Applications, Proceedings., 11th IAPR International Conference on
Conference_Location :
The Hague
Print_ISBN :
0-8186-2910-X
DOI :
10.1109/ICPR.1992.201518