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.

中文翻译：

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基于自动图像识别的港口运输通道异物识别技术

在港口运输中，由于异物的影响，运输车辆极易在运输过程中造成不良状况，目前的异物检测仍采用人工方法进行。在此基础上，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采集并分析视频图像以进行异物识别。我们使用极限中值滤波来执行图像噪声处理，并对传统的Canny边缘检测算法进行改进，以获得针对Canny算子的改进的边缘检测方法。该算法用于执行图像边缘检测，而图像灰度直方图用于增强异物图像处理。结合实验分析，