| Abstract:In view of the current X-ray image security inspection method for dangerous goods identification, which does not collect fuzzy static image targets, resulting in poor security inspection of dangerous goods images, low recognition rate of dangerous goods, and long recognition time, an X-ray image security inspection based on VR technology is proposed. Automatic identification method of dangerous goods. Obtain security inspection dangerous goods imaging through X-rays, use VR technology to acquire fuzzy static image targets, use optical imaging principles to process fuzzy static image targets in layers, acquire fuzzy static image targets' brightness layer and detail layer, and compress fuzzy static image targets for adaptive partitioning. Realize the target reproduction of dangerous goods images, extract the texture features of dangerous goods images based on the Walsh transform method, build a BP neural network model, repeatedly adjust the weights and thresholds and perform training to ensure that the output error is minimized, and realize the X-ray image security inspection of dangerous goods auto recognition. The experimental results show that the proposed method has a better presentation effect of dangerous goods images for security inspection, can effectively improve the recognition rate of dangerous goods, shorten the time of dangerous goods recognition, and have good dangerous goods recognition performance. |
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