铁路轨道裂纹检测的计算机视觉分析

S. Saha, S. Karmakar, Debasmita Manna
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引用次数: 1

摘要

本文提出了一种利用计算机视觉检测铁路轨道裂缝的实验工作。采用边缘检测处理和数据集训练方法来实现这项工作。边缘检测是一种图像处理方法,用于发现图像中物体的边界。数据集包括各种模板、图像和数据,用于训练算法和模型,使其能够准确预测最终结果。这对于分析铁路轨道裂缝和故障,避免事故的发生具有重要意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of Railroad Track Crack Detection using Computer Vision
In this study, an experimental work is presented to detect the cracks in the railroad tracks using computer vision. Edge Detection process and Dataset Training methods are adopted for implementation of this work. Edge Detection is an image processing methodology for spotting the boundaries of objects within images. Dataset includes various templates, images and data which is used to train the algorithm and model so it can accurately predict the final outcome. This study is essential to analyze the cracks and faults in the railroad tracks to avoid accidents.
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