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A Hardware Implementation for Colour Edge Detection Using Prewitt-Inspired Filters Based on Geometric Algebra

机译:基于几何代数的PREWITT-Inspired滤波器的彩色边缘检测硬件实现

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摘要

Geometric algebra (GA) is a powerful mathematical tool that offers intuitive solutions for image-processing problems, including colour edge detection. Rotor-based and Prewitt-inspired Sangwine (RBS and PIS) filters are amongst the efficient algorithms based on GA operators for solving colour edge detection problem. Algorithms in GA framework have enormous computational load that limits the general-purpose processors' ability to execute them in reasonable time. Recently, some specialized hardware architectures, called full-hardware implementations, are proposed. These architectures, such as ConformalALU co-processor, are able to execute GA algorithms in acceptable time with the moderate use of computational resources. So far, all colour edge detection hardwares in GA framework exploited RBS filters. Nevertheless, this novel work presents a full-hardware architecture for efficient execution of PIS filters. PIS filters consume less computational resources and are faster to execute. For comparison, the hardware obtained by Gaalop pre-compiler uses twice as much resources with the same speed as the proposed hardware. As an evidence of faster operation, the proposed hardware is able to execute the edge detection algorithm almost 315 times faster than a GA co-processor, with only 2.5 times of its resources.
机译:几何代数(GA)是一种强大的数学工具,可为图像处理问题提供直观的解决方案,包括彩色边缘检测。基于转子和PREWITT的Sangwine(RBS和PIS)滤波器是基于GA运算符的高效算法,用于解决彩色边缘检测问题。 GA框架中的算法具有巨大的计算负载,可以限制通用处理器在合理的时间内执行它们的能力。最近,提出了一些名为全硬件实现的专用硬件架构。这些架构(例如Conformalalu)协处理器都能够在可接受的时间内执行GA算法,以适度使用计算资源。到目前为止,GA框架中的所有彩色边缘检测硬件都会利用RBS过滤器。尽管如此,这部新颖的工作提供了一种用于高效执行PIS过滤器的全硬件架构。 PIS过滤器消耗较少的计算资源,并且执行更快。为了比较,Gaalop预编译器获得的硬件使用两倍的资源,与所提出的硬件相同的速度。作为更快操作的证据,所提出的硬件能够比GA协处理器快速执行边缘检测算法,只有2.5倍的资源。

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