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Image Feature Recognition of Railway Truck Based on Machine Learning

Image feature recognition [1] is an important area of artificial intelligence [2]. It refers to the technique of using computers to process, analyze, and understand images, aimed at recognizing targets and objects in various modes. Based on the machine learning [3] algorithm, this paper uses the deep learning model to detect the truck number area under the complex background interference, and then uses the convolutional neural network to design the dynamic segmentation method for recognizing the truck number. The deep learning model Faster Regions with Convolutional Neural Networks (RCNN) [4] can accurately detect the truck number area and make a good foundation for subsequent recognition. The convolutional neural network designed with single character overcomes the interference of illumination and complex background, which effectively solves the problem of truck number discontinuity. Finally, through multiple experiments, in the complex background, the proposed method in this paper has stronger robustness and higher recognition rate than traditional image recognition methods.