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首页> 外文期刊>International Journal of Pattern Recognition and Artificial Intelligence >SHAPE RECOGNITION USING A FIXED-SIZE VLSI ARCHITECTURE
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SHAPE RECOGNITION USING A FIXED-SIZE VLSI ARCHITECTURE

机译：使用固定大小的VLSI体系结构进行形状识别

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摘要

Shape recognition is an important research area in pattern recognition. It also has wide practical applications in many fields. An attribute grammar approach to shape recognition combines both the 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~3) where n is the length of an input string. When the problem size is very large it needs much more computing time, therefore a high speed parallel shape recognition is necessary to meet the demands of some real-time applications. This paper presents a parallel shape recognition algorithm and also discusses the algorithm partition problem as well as its implementation on a fixed-size VLSI architecture. The proposed algorithm has time complexity O(n~3/k~2) if using k x k processing elements. When k = n, its time complexity is O(n). The experiment has been conducted to verify the performance of the proposed algorithm. The correctness of the algorithm partition and the behavior of the proposed VLSI architecture have also been proved through the experiment. The results indicate that the proposed algorithm and the VLSI architecture could be very useful to imaging processing, pattern recognition and related areas, especially for real-time applications.
机译：形状识别是模式识别的重要研究领域。它还在许多领域具有广泛的实际应用。一种用于形状识别的属性语法方法结合了语法和统计方法的优点，并使形状识别更加准确和有效。但是，使用属性语法的顺序形状识别算法的时间复杂度为O（n〜3），其中n是输入字符串的长度。当问题的大小很大时，它需要更多的计算时间，因此需要高速并行形状识别才能满足某些实时应用程序的需求。本文提出了一种并行形状识别算法，并讨论了算法划分问题及其在固定大小的VLSI架构上的实现。如果使用k x k个处理元素，则该算法的时间复杂度为O（n〜3 / k〜2）。当k = n时，其时间复杂度为O（n）。已经进行了实验以验证所提出算法的性能。实验还证明了算法划分的正确性和所提出的VLSI体系结构的行为。结果表明，所提出的算法和VLSI体系结构可能对成像处理，模式识别及相关领域特别是实时应用非常有用。

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