Color histogram based vehicle body color identification method

A color histogram and color recognition technology, which is applied in character and pattern recognition, image enhancement, image analysis, etc., can solve the problems of positioning algorithm influence, body color distortion, large limitations, etc., to improve real-time performance and result stability performance, high recognition accuracy, and strong robustness

Inactive Publication Date: 2015-12-16
UNIV OF ELECTRONIC SCI & TECH OF CHINA
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Problems solved by technology

[0004] 1. The color of the car body is easily disturbed by external noise such as light, smog, and different weather, resulting in color distortion;
[0005] 2. The color of the vehicle is complex and changeable (the body color is rich and colorful, and the color of some vehicles is relatively rare);
[0006] 3. It is difficult to segment and locate movin

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  • Color histogram based vehicle body color identification method

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Embodiment Construction

[0035] For the convenience of describing the content of the present invention, some terms are explained here at first:

[0036] Body color recognition system. Refers to the vehicle that can detect the monitored road surface and automatically extract the body color information (including red, black, white, silver white, yellow, green, blue and other colors) and identify it.

[0037] Lab color space. Lab is a color space, that is, a color model, which was established on the basis of the international standard for color measurement formulated by the International Commission on Illumination (CIE) in 1931, so it is also called CIELAB space. L indicates lightness, a indicates the range from magenta to green, and b indicates the range from yellow to blue. Lab describes all the colors that people can see, and describes the display of colors, so Lab is regarded as a device-independent color model.

[0038] Morphological operations on images. Mathematical morphology analyzes images ...

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Abstract

The invention provides a color histogram based vehicle body color identification method. The method comprises three main steps of license plate positioning, vehicle body color feature region positioning and vehicle body color identification. The method particularly comprises: firstly, determining a license plate position through a license plate identification technology, and detecting a coarse region of vehicle body color through the height, width and position coordinate information of a license plate; preprocessing the region of the vehicle body color to reduce external environment interferences; further searching the preprocessed coarse region of the vehicle body color to obtain an accurate feature region of the vehicle body color; and converting the feature region into a Lab color space, extracting a color histogram from the Lab space, and performing vehicle body color training and identification by using a nonlinear SVM. The method is capable of intelligently processing traffic vehicle videos and images and automatically identifying the vehicle body color. Compared with other schemes in the same field, the method has very high identification accuracy and is high in robustness in a complicated environment.

Description

technical field [0001] The invention belongs to digital image processing technology, in particular to computer vision recognition technology. Background technique [0002] Therefore, in the intelligent transportation system, while the license plate is recognized, other auxiliary information of the vehicle is also required, such as body color, model, vehicle logo, etc. [0003] At present, there are relatively few studies on body color recognition, and the technology is still immature, and its recognition accuracy is far inferior to that of license plate recognition. The main reasons affecting the recognition rate: [0004] 1. The color of the car body is easily disturbed by external noise such as light, smog, and different weather, resulting in color distortion; [0005] 2. The color of the vehicle is complex and changeable (the body color is rich and colorful, and the color of some vehicles is relatively rare); [0006] 3. It is difficult to segment and locate moving veh...

Claims

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Application Information

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IPC IPC(8): G06T7/40G06T7/20G06K9/62
CPCG06T2207/10024G06T2207/10016G06T2207/30236G06F18/2411
Inventor 解梅黄成挥于国辉罗招材
Owner UNIV OF ELECTRONIC SCI & TECH OF CHINA
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