多维改进Canny算法在5G智能电网图像智能识别与监控中的应用研究

Dong Wu, Liu Xu, Tang Wei, Zhou Qian, Cai Cheng, Guoyi Zhang, Hailong Zhu
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引用次数: 0

摘要

基于贵州电网5G应用与实践,针对5G网络采集的海量数据信息,如何基于图像智能识别算法高效、快速地识别关键信息并实现报警返回是本文的核心。针对上述图像边缘检测问题,本文提出了一种改进的多维Canny算法。每个阶段分别采用小波阈值去噪、改进的四方向Sobel模板、角度插值、融合Otsu算法、遗传算法和双低阈值算法以及二次形态学处理。通过搭建仿真平台,验证了基于Canny的多维改进算法不仅继承了原算法的优点,而且在算法效率、均方误差、峰值信噪比、结构相似度等方面都比传统Canny算法有更好的表现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research of Multi-dimensional Improved Canny Algorithm in 5G Smart Grid Image Intelligent Recognition and Monitoring Application
Based on the 5G application and practice of Guizhou power grid, aiming at the massive data information collected by 5G network, how to identify the key information efficiently and quickly based on the image intelligent recognition algorithm and realize the alarm return is the core of this paper. In view of the above image edge detection problems, this paper proposes an improved multi-dimensional Canny algorithm. In each stage, wavelet threshold denoising, improved 4-direction Sobel template, angle interpolation, fusion Otsu algorithm, genetic algorithm and double low threshold algorithm, and secondary morphological processing are used. By building a simulation platform, it is verified that the multi-dimensional improved algorithm based on Canny not only inherits the advantages of the original algorithm, but also has better performance in the aspects of algorithm efficiency, mean square error, peak signal-to-noise ratio and structural similarity compared with the traditional Canny algorithm.
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