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Improvement and parallel implementation of canny edge detection algorithm based on GPU

机译:基于GPU的Canny边缘检测算法的改进和并行实现

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Being an effective edge detector with single-pixel response, Canny operator has been widely used in accurately abstracting the edge information in image processing. However, taking its 4-step process into account, its real-time implementation based on CPU has become a significant problem, especially for the part of the edge tracing, which consumes a large amount of computing time. To solve the problem, GPU will be used in this paper for sake of its powerful ability of parallel processing while a new Canny operator is proposed with the introduction of parallel breakpoints detection and edge tracing without recursive operations. Experimental results show that, the improved Canny operator has obtained a high real-time performance of edge detection in image processing.
机译:作为具有单像素响应的有效边缘检测器,Canny算子已广泛用于在图像处理中准确抽象边缘信息。但是,考虑到其4步处理,基于CPU的实时实现已成为一个重大问题,特别是对于边缘跟踪而言,这会占用大量计算时间。为了解决这个问题,本文将使用GPU,因为它具有强大的并行处理能力,同时提出了一种新的Canny运算符,它引入了并行断点检测和边缘跟踪功能,而无需递归操作。实验结果表明,改进的Canny算子在图像处理中获得了很高的边缘检测实时性。

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