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A vehicle color recognition method based on bp neural network

A BP neural network and color recognition technology, which is applied in the field of vehicle color recognition based on BP neural network, can solve the problems that the correct vehicle color area cannot be extracted, and the color recognition of the front and rear of the car cannot be considered.

Active Publication Date: 2020-09-15
ZHEJIANG UNIV OF TECH
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AI Technical Summary

Problems solved by technology

[0004] To sum up, the current method has the following deficiencies in the color recognition of vehicles: (1) Sometimes the correct color area of ​​the vehicle cannot be extracted; (2) The color recognition of the front and rear of the car cannot be considered; Unrecognizable color, should not use a single absolute color as the final recognition result

Method used

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  • A vehicle color recognition method based on bp neural network
  • A vehicle color recognition method based on bp neural network
  • A vehicle color recognition method based on bp neural network

Examples

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Embodiment Construction

[0057] A specific implementation method of a vehicle color recognition method based on a BP neural network will be described in detail below in conjunction with an embodiment. It should be understood that the specific examples described here are only used to explain the present invention, not to limit the present invention.

[0058] The concrete process of a kind of vehicle color recognition method based on BP neural network of the present invention is as follows figure 1 As shown, the specific steps are as follows:

[0059] Step 1: Define the body color set as C={c 1 ,c 2 ,c 3 ,c 4 ,c 5 ,c 6 ,c 7 ,c 8 ,c 9 ,c 10}={black, gray, white, pink, brown, red, yellow, green, blue, purple}, and establish the corresponding color data set;

[0060] Step 2: Construct a BP neural network for color classification and use the color data set in step 1 for training, specifically:

[0061] Step 2.1: Use a three-layer BP neural network with one hidden layer, the number of neurons in ...

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Abstract

The invention discloses a vehicle color recognition method based on BP neural network. Compared with the existing vehicle color recognition method, the invention uses computer vision technology to extract vehicle color features, combine HSV color space model and pass BP neural network Classification solves the problem of vehicle color recognition, and can take into account the recognition of the front and rear of the car at the same time, improving the traditional working mode of distinguishing cars by license plate, and providing a reliable solution for combating illegal and criminal activities such as car deck, multiple license plates, and fake license plates. Help, further improve the reliability of intelligent transportation, save a lot of labor costs.

Description

technical field [0001] The invention belongs to the field of computer vision technology and image processing technology, in particular to a vehicle color recognition method based on BP neural network. Background technique [0002] With the rapid development of science and technology and social economy, people's living standards continue to improve, the number of vehicles is also increasing rapidly, urban road traffic problems are becoming more and more prominent, and various road traffic problems follow one after another. Traditional road monitoring methods cannot meet the requirements, and modern intelligent traffic control systems have become the development trend of global road traffic in the future and the advanced symbol of modern cities. In recent years, illegal activities such as blocking license plates and car decks have emerged in an endless stream. Relying on license plate recognition alone can no longer adapt to the current traffic situation. Therefore, vehicle co...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/90G06K9/62G06K9/00
CPCG06T7/90G06T2207/20084G06T2207/20081G06T2207/20032G06T2207/30252G06T2207/10024G06V20/52G06V2201/08G06F18/241
Inventor 高飞倪逸扬蔡益超金一鸣卢书芳毛家发
Owner ZHEJIANG UNIV OF TECH
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