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Co-Design System for Template Matching Using Dedicated Co-Processor and Cuckoo Search

机译:使用专用协处理器和杜鹃搜索的模板匹配协同设计系统

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摘要

Template matching is an important method used for object tracking, in order to find a given-pattern within a frame sequence. Pearson's Correlation Coefficient (PCC) is widely used to quantify the similarity between two images. Since this coefficient calculus is computed for each image pixel, it entails a computationally expensive process. In this article, an embedded co-design system is proposed, which implements the template matching, in order to accelerate this process. The dedicated co-processor, responsible for performing the PCC computation, is used in two configurations: serial and pipeline. Cuckoo Search (CS) is used to improve the search for the maximum correlation point of the image and the used template. The search process is implemented in software and is run by an embedded general-purpose processor. The performance results are compared to those obtained through Particle Swarm Optimization (PSO) using the same hardware approach.
机译:模板匹配是用于对象跟踪的重要方法,以便在帧序列中找到给定的模式。皮尔逊相关系数(PCC)被广泛用于量化两个图像之间的相似性。由于此系数演算是针对每个图像像素计算的,因此需要进行大量计算。本文提出了一种嵌入式协同设计系统,该系统可以实现模板匹配,从而加快该过程。负责执行PCC计算的专用协处理器以两种配置使用:串行和流水线。布谷鸟搜索(CS)用于改善对图像和所用模板的最大相关点的搜索。搜索过程由软件实现,并由嵌入式通用处理器运行。使用相同的硬件方法,将性能结果与通过粒子群优化(PSO)获得的结果进行比较。

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