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Foreign object recognition technology for port transportation channel based on automatic image recognition

机译:基于自动图像识别的港口运输信道异物识别技术

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摘要

Abstract In the port transportation, the transportation vehicle is extremely easy to cause a bad condition in the transportation process due to the influence of foreign matter, and the current foreign matter detection is still carried out by manual methods. Based on this, this study is based on the automatic image recognition technology, using the binocular imaging system for video collection and analyzing the video images for foreign object recognition. We use extreme median filtering to perform image noise processing and improve the traditional Canny edge detection algorithm to obtain an improved edge detection method for Canny operator. The algorithm is used to perform image edge detection, and the image gray histogram is used to enhance the foreign object image processing. Combined with the experimental analysis, the detection method of this study has certain effects, which can be used for foreign object identification in port transportation channels and can provide theoretical reference for subsequent related research.
机译:摘要在港口运输中,由于异物的影响,运输车辆在运输过程中极易地引起不良状态,并且目前的异物检测仍然通过手动方法进行。基于此,本研究基于自动图像识别技术,使用双目成像系统进行视频收集并分析视频图像进行异物识别。我们使用极端中值滤波来执行图像噪声处理,并改善传统的Canny Edge检测算法,以获得Canny算子的改进边缘检测方法。该算法用于执行图像边缘检测,并且使用图像灰度直方图来增强异物图像处理。结合实验分析,本研究的检测方法具有一定的效果,可用于端口运输通道中的异物识别,并可提供后续相关研究的理论参考。

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