Attribute grammar for shape recognition and its VLSI implementation

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(n/sup 3/) 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(n/sup 3//k/sup 2/). 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.<>