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Study of Image Recognition Used for Unattended Substation

机译:用于无人参与变电站的图像识别研究

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It is a trend to construct unattended substation in power system nowadays. This paper systematically analyses the superiority and limitation of MATLAB and Visual C++ and illustrates how to compile m-files to cpp-files by MATLAB engines and integrate cpp-files code into existing C++ projects by Visual C++ to realize intelligent function on image recognition used for unattended substation. The intelligent function can effectively test illegal intrusion and fires through the detection and recognition of moving goals by three-image difference method and self-adapting threshold value segmentation algorithm and detect situations of disconnection link by use of image crop and image index processing and give warnings to alarm system. Because of lacking of brightness of image or nonlinear brightness and being influenced by kinds of noise, this paper determines to adopt contrast enhanced algorithm and high-frequency enhanced algorithm to repair grey-scale distribution and uses median filtering to remove noise of image. In the end, this paper brings forward the expectation about the image recognition of the unattended substation. When non-uniform of image illumination distribution, grey-scale of background changes largely and image segmentation has not the fittest threshold, so the paper uses self-adapting threshold segmentation algorithm to gain the image segmentation.
机译:现在是在电力系统中构建无人值守变电站的趋势。本文系统地分析了Matlab和Visual C ++的优势和限制,并说明了如何通过Matlab引擎编译到CPP文件的CPP文件,并通过Visual C ++将CPP-Files代码集成到现有的C ++项目中,以实现用于图像识别的智能功能无人值守的变电站。智能功能可以通过三个图像差法和自适应阈值分割算法检测和识别移动目标的检测和识别智能函数,并通过使用图像裁剪和图像索引处理来检测断开链路的情况,并给警告检测断开链路情况到报警系统。由于缺乏图像或非线性亮度的亮度和受噪声种类的影响,因此采用对比增强算法和高频增强算法来修复灰度分布,并使用中值滤波去除图像的噪声。最后,本文提出了关于无人参与变电站的图像识别的期望。当图像照明分布的不均匀时,背景的灰度范围很大程度上变化,图像分割没有最适合的阈值,因此纸张使用自适应阈值分割算法来获得图像分割。

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