Vehicle model recognition method of the same brand based on spatial location information

Abstract

The invention relates to a method for identifying vehicle types of vehicles of the same brand based on spatial position information. The method includes: collecting images of the vehicles; performing histogram equalization on the images of the vehicles; setting the size of the license plate, and adjusting the histogram The image after image equalization is stretched and rotated; the feature area of ​​N vehicle models to be tested is extracted according to the position of the corrected image relative to the license plate; the feature vector of each feature area is calculated; the minimum distance classifier is used to classify each feature vector Classify and compare with the reference feature vector of the brand vehicle in the database to identify the specific model. The method of the invention extracts the feature area of ​​the license plate and then identifies the relevant parameters of the feature area, thereby improving the recognition accuracy of the vehicle type.

Description

technical field [0001] The invention belongs to the field of image processing in intelligent transportation, and in particular relates to a method for identifying vehicle types of vehicles of the same brand based on spatial position information. Background technique [0002] At this stage, intelligent transportation has higher and higher requirements for vehicle information, and identifying vehicle information has high practical value. At present, there are mainly pattern recognition methods based on physical parameters and pattern recognition methods based on image processing. The pattern recognition method based on physical parameters obtains some physical parameters of the vehicle through sensors such as coils, but can only recognize the size of large cars, medium-sized cars, small cars, etc., but cannot identify the specific type of vehicle information, such as Cars of different brands, and different models under the same brand car, etc. The image-based vehicle identif...

AI Technical Summary

Problems solved by technology

It has the following problems: it is very difficult to directly extract the feature area, it is difficult to control the extraction accuracy, it is easy to make mistakes, and the feature areas segmented by different models may be very similar, resulting in recognition errors

Therefore, direct segmentation and extraction feature recognition often leads to the recognition rate not meeting the requirements, and the robustness of the algorithm is not enough

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