一种改进的动态双阈值Canny边缘检测算法

Zhikang Xiao, Yang Zou, Zhen Wang
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引用次数: 7

摘要

随着产业升级,机器人迫切需要对运动目标进行高速跟踪。因此,机器视觉技术中的检测算法需要改进。针对传统Canny边缘检测算法需要确定高低阈值的问题,提出了一种改进的动态双阈值Canny算法。不断增大阈值的大小,以图像边缘闭合区域的大小作为标准,最终确定最佳阈值,以达到最佳检测效果。实验结果表明,改进的动态双阈值Canny算法不仅边缘检测效果比传统算法平均提高了9%,而且检测到的图像信息更完整,具有更强的适应性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An improved dynamic double threshold Canny edge detection algorithm
With the upgrade of the industry, robots urgently need to track moving targets at high speed. Therefore, the detection algorithms in machine vision technology need to be improved. Aiming at the problem that high and low thresholds need to be fixed in traditional Canny edge detection algorithm, an improved dynamic double threshold Canny algorithm is proposed. Constantly increasing the size of the threshold, Using the size of the area where the image edge is closed as a standard, finally to determine the best threshold, In order to achieve the best detection effect. Experimental results show that, Improved dynamic double threshold Canny algorithm not only improves the edge detection effect by 9% on average compared with the traditional algorithm, but also detects more complete image information and has stronger adaptability.
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