Based on infrared laser Imaging research on foreign objects detection between subway door

With rapid development of rail transport in our country, more and more people choose because of on time, fast and convenient. Safety of the subway is urgent with passenger increasing, and it's very important to inspire hidden danger. The paper proposed The auto-inspection method based on Infrared Laser Imaging and Deep Learning to detect foreign objects between subway doors and the platform screen doors(PSDs). Fast-RCNN Algorithm based on TensorFlow Deep Learning frame was adopted and the image information were fused with classification model, vgg16. The detecting system was built and experiments were made and analyzed. The experimental results showed that this system and method was robust to The illumination variations and focussing. The system is simple and cost-effective and The algorithm is promising for detecting accuracy. The method and technology can be potentially applied for The subway safety detection.