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A Highway Vehicle Detection System of Green Channel Based on Radar Echo

Author: MengHongFei
Tutor: NiuJianQiang
School: Henan University of Science and Technology
Course: Applied Computer Technology
Keywords: Radar echo Feature Extraction Texture analysis BP algorithm
CLC: TP274
Type: Master's thesis
Year: 2011
Downloads: 32
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Abstract


In recent years, with the national \However, traditional manual testing method is not only time-consuming, and inefficient; easy to miss part of the fake \So, how to design a fast and efficient lossless the highway detection system with a very important theoretical and practical significance. This article is the drawbacks of manual inspection method, as well as various non-destructive detection technology advantages and disadvantages based on proposed based on radar echo Freeway Green Corridor vehicle detection program. The focus of the study is to detect the radar echo for carriage, entrainment and entrainment of prohibited items is not radar echo, detailed study of the radar echo characteristics extraction algorithm and recognition algorithms, such as co-occurrence matrix based on secondary Statistics gray, BP network image recognition algorithms automatically analyze and judge the radar echo of the compartment. This paper introduces the radar echo feature extraction, the pretreatment before feature extraction, which mainly includes the two parts of the analysis of the pseudo-color processing and gray. Entrainment of prohibited drug and no differences entrained prohibited drug, the radar echoes reflected back, pseudo-color given different colors for different radar echo data matrix can improve the human eye's ability to distinguish, then back on the radar Matlab program The wave a gradation analysis identify different echo images of the gray level of the degree of concentration as well as the probability distribution of each gradation, the final feature extraction. Its purpose is to image classification. There are many ways to describe the image features, including image texture features is an important feature in the image analysis. Feature extraction algorithm is based on the amount of secondary statistical thinking gray co-occurrence matrix extracted based on the radar echo texture parameters in different situations as identifying characteristics. Secondly, detailed radar echo identification, and in pattern recognition, image identification is a relatively difficult recognition mode. There are a variety of image recognition algorithm. The in-depth analysis of the merits of multiple image recognition algorithm, The radar echo own characteristics and the actual situation of the scene, the introduction of neural networks in the radar echo identification system. Focus on BP neural network algorithm. Slow for BP algorithm convergence speed, and can not converge to the global minimum, it is difficult to determine the hidden layer, and the lack of the number of hidden nodes to improve, then BP network model established to identify radar echo. Finally, many experiments and practical applications show that the system can effectively judge the ability to identify and classify performance vehicle, the recognition rate is above 75%. The system can implement intelligent vehicle detection and recognition, improve test accuracy, reduce labor intensity of inspection personnel.

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CLC: > Industrial Technology > Automation technology,computer technology > Automation technology and equipment > Automation systems > Data processing, data processing system
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