A VLSI architecture for object recognition using tree matching

K. Sitaraman, N. Ranganathan, A. Ejnioui
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引用次数: 4

Abstract

The problem of tree pattern matching for object recognition in images is computationally intensive in nature. In two-dimensional images, the objects can be represented through multiscale decomposition as tree structures. The pattern tree representing an object can be matched with a subject tree representing an image in order to detect the objects within the image. In this paper, we describe a new systolic algorithm and its realization as a VLSI chip for tree pattern matching. The hardware algorithm is based on a linear array of processing elements (PEs) where the pattern matching is done in a pipelined fashion relying on nearest-neighbor communication between the PEs and the subject and pattern trees of arbitrary length can be processed using a fixed size PE array. The algorithm has an improved execution time of O(/spl lceil/m/a/spl rceil/n) required to perform the matching where in, a and n are the sizes of the pattern tree, processor array, subject tree respectively. A prototype CMOS VLSI chip implementing the proposed algorithm has been designed and verified It is shown that the hardware algorithm proposed in this work represent a significant improvement in terms of computational complexity, data flow, and architecture over the ones previously proposed for this problem.
基于树匹配的超大规模集成电路目标识别体系结构
图像中目标识别的树模式匹配问题本质上是计算密集型的。在二维图像中,物体可以通过多尺度分解表示为树形结构。表示对象的模式树可以与表示图像的主题树相匹配,以便检测图像中的对象。本文描述了一种新的树型匹配的压缩算法及其在VLSI芯片上的实现。硬件算法基于处理元素的线性阵列(PE),其中模式匹配以流水线方式完成,依赖于PE与主题之间的最近邻通信,并且可以使用固定大小的PE阵列处理任意长度的模式树。该算法将执行匹配所需的执行时间缩短为O(/spl ceil/m/a/spl ceil/n),其中in、a、n分别为模式树、处理器阵列、主题树的大小。设计并验证了实现所提算法的原型CMOS VLSI芯片。结果表明,本工作中提出的硬件算法在计算复杂度、数据流和架构方面比先前提出的算法有了显著的改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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