The consumption of seaweed is increasing year by year worldwide. Therefore, the foreign object inspection of seaweed is becoming increasingly important. Seaweed is mixed with various materials such as laver and sargassum fusiforme. So it has various colors even in the same seaweed. In addition, the surface is uneven and greasy, causing diffuse reflections frequently. For these reasons, it is difficult to detect foreign objects in seaweed, so the accuracy of conventional foreign object detectors used in real manufacturing sites is less than 80%. Supporting real-time inspection should also be considered when inspecting foreign objects. Since seaweed requires mass production, rapid inspection is essential. However, hyperspectral imaging techniques are generally not suitable for high-speed inspection. In this study, we overcome this limitation by using dimensionality reduction and using simplified operations. For accuracy improvement, the proposed algorithm is carried out in 2 stages. Firstly, the subtraction method is used to clearly distinguish seaweed and conveyor belts, and also detect some relatively easy to detect foreign objects. Secondly, a standardization inspection is performed based on the result of the subtraction method. During this process, the proposed scheme adopts simplified and burdenless calculations such as subtraction, division, and one-by-one matching, which achieves both accuracy and low latency performance. In the experiment to evaluate the performance, 60 normal seaweeds and 60 seaweeds containing foreign objects were used, and the accuracy of the proposed algorithm is 95%. Finally, by implementing the proposed algorithm as a foreign object detection platform, it was confirmed that real-time operation in rapid inspection was possible, and the possibility of deployment in real manufacturing sites was confirmed.

中文翻译：

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使用 VNIR 高光谱成像的海藻快速异物检测系统

海藻的消费量在世界范围内逐年增加。因此，海藻异物检测变得越来越重要。海藻与紫菜和马尾藻等各种材料混合。所以即使在同一种海藻中，它也有不同的颜色。此外，表面不平整、油腻，经常造成漫反射。由于这些原因，很难检测到海藻中的异物，因此在实际制造现场使用的常规异物检测器的准确度不到80%。异物检测时还应考虑支持实时检测。由于海藻需要大量生产，因此快速检验必不可少。然而，高光谱成像技术通常不适合高速检测。在这项研究中，我们通过使用降维和使用简化操作来克服这个限制。为了提高精度，所提出的算法分两个阶段进行。首先是用减法的方法来清晰地区分海藻和传送带，同时也检测一些比较容易检测的异物。其次，根据减法方法的结果进行标准化检查。在此过程中，所提出的方案采用减法、除法、一一匹配等简化无负担的计算，实现了精度和低延迟性能。在评估性能的实验中，使用了60个正常海藻和60个含有异物的海藻，所提算法的准确率为95%。最后，