基于VR技术的X射线图像安检危险品自动识别

针对当前X射线图像安检危险品识别方法未采集模糊静态图像目标，导致安检危险品图像呈现效果较差、危险品识别率较低、识别时间较长的问题，提出了基于VR技术的X射线图像安检危险品自动识别方法。通过X射线获取安检危险品成像，采用VR技术采集模糊静态图像目标，利用光学成像原理分层处理模糊静态图像目标，获取模糊静态图像目标亮度层和细...

Automatic Identification of Dangerous Goods in X-ray Image Security Inspection Based on VR Technology

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 automatic identification method of dangerous good in X-ray image security inspection based on VR technology is proposed. Obtaining security inspection dangerous goods imaging through X-rays, using VR technology to acquire fuzzy static image targets, using optical imaging principles to process fuzzy static image targets in layers, acquiring fuzzy static image targets'' brightness layer and detail layer, and compressing fuzzy static image targets for adaptive partitioning, realizing the target reproduction of dangerous goods images. Extracting the texture features of dangerous goods images based on the Walsh transform method, building a BP neural network model, repeatedly adjusting 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.