Abstract
With the development of machine learning for decades, there are still many problems unsolved, such as image recognition and location detection, image classification, image generation, speech recognition, natural language processing and so on. In the field of deep learning research, the research on image classification has always been the most basic, traditional and urgent research direction. At the same time, computer intelligent image recognition technology is also conducive to gradually better respond to the development of international indicators, and promote the development and progress of various fields. Therefore, image processing technology based on machine learning has been widely used in feature image, classification, segmentation and recognition, and is a hot spot in various fields. However, due to the complexity of video images and the distribution of objects in different application backgrounds, the classification accuracy becomes important and difficult. In the paper transportation industry, image recognition technology is applied to license plate recognition to extract license plate from complex background, segment license plate characters and recognize characters, and construct a machine learning non license plate automatic generation algorithm, which may improve the efficiency of non license plate recognition. The diversity and high generation speed of license plate training sample set can achieve the purpose of effectively training strong classifier. By using genetic algorithm to optimize BP neural network to classify license plate information, the anti-interference ability and license plate recognition accuracy are improved to a certain extent.
Highlights
Machine Learning (ML, Machine Learning) [1,2,3,4,5] is a fundamental and critical issue in the field of image processing [6, 7], especially in the field of massive image processing, machine learning methods can be from complex data [8]
This paper identifies the license plate based on the machine learning method, and classifies the sample using BP neural network trained by genetic algorithm [30]
As an important method in the field of artificial intelligence, machine learning has been widely used in traffic identification research in recent years
Summary
Machine Learning (ML, Machine Learning) [1,2,3,4,5] is a fundamental and critical issue in the field of image processing [6, 7], especially in the field of massive image processing, machine learning methods can be from complex data [8]. Image processing technology based on machine learning has been widely used in image classification, segmentation, and recognition [10]. It is a hotspot of research and research in various fields. With the rapid development of modern technology and the application of video images in various fields of life, machine learning is important for the processing of video images.
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