Front face feature-based vehicle type recognition method

Abstract

The invention provides a front face feature-based vehicle type recognition method, which comprises the following parts: S01, executing an image histogram information-based road surface vehicle automatic extraction method: analyzing road surface images sent back by a traffic checkpoint on a road, and extracting possible vehicle areas in the road surface images by adopting a monocular image analysis method; S02, executing a color and gradient information-fused vehicle front face interception method: analyzing the color and the gradient information of a target in vehicle area images obtained in the step S01 to complete the interception of a vehicle front face; S03, performing heterogeneous sample analysis-based vehicle type online training, and establishing vehicle templates of various vehicle types; S04, executing a vehicle front face feature subspace-based vehicle type judging method: matching the vehicle front face intercepted in the step S02 and the vehicle templates obtained in the step S03 to obtain the judging decision of the vehicle types. According to the front face feature-based vehicle type recognition method disclosed by the invention, the automatic recognition of the vehicle types can be accurately performed, and the daily work of relevant departments requiring vehicle type information is greatly facilitated.

Description

technical field [0001] The invention relates to the technical field of image recognition, in particular to a vehicle type recognition method based on vehicle front face features. Background technique [0002] With the development of artificial intelligence, automatic control and pattern recognition and other fields, intelligent transportation system came into being and achieved great development. Intelligent identification and classification of vehicle types has always been an important part of intelligent transportation systems. Accurate identification of vehicle types is of great significance to the determination of highway tolls, the management of large parking lots, and the monitoring and control of highway traffic. [0003] Traditional vehicle classification detectors mainly include piezoelectric detectors, infrared detectors, magnetic induction detectors and ultrasonic detectors, which are easily affected by other external unstable factors, and mostly estimate the len...

AI Technical Summary

Problems solved by technology

In the current vehicle type discrimination, most feature quantities such as vehicle length, width, height, and invariant moments are extracted from video images through noise reduction processing and edge detection, and then pattern recognition is performed to determine the vehicle model, but only Judging the general type of vehicle, such as trucks, cars, etc., cannot realize the identification of the specific model corresponding to the vehicle

[0005] Since there are nearly 10,000 models corresponding to the same type of vehicle, it is very challenging to identify the specific model of the vehicle, and there are few related researches

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