Machine Vision-Based Hook Defect Detection

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Due to the harsh working environment of crane equipment, regular safety inspection is essential. The hook is one of the most frequently used parts of crane equipment. Therefore, if the hook lacks regular and standardized safety inspection, it can easily cause casualties. However, traditional machine vision techniques still face many challenges, making it difficult to extract the target object from the complex scene. In this paper, we propose a combination of machine vision techniques based on deep learning and traditional methods to extract hooks from complex construction site scenes and detect whether the hooks meet the criteria for proper operation.