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Vehicle logo identification method fusing sliding window and Faster R-CNN

A convolutional neural network and sliding window technology, applied in the field of vehicle logo positioning and recognition, can solve problems such as the inability to roughly locate the car logo, the inability to extract the area of ​​the car logo, and the slow recognition speed

Active Publication Date: 2018-03-13
ZHEJIANG UNIV OF TECH +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] To sum up, the current method has the following deficiencies in the identification of vehicle logos: (1) the vehicle logo cannot be roughly positioned when there is no license plate; (2) the recognition speed is slow; (3) sometimes the correct car logo area

Method used

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  • Vehicle logo identification method fusing sliding window and Faster R-CNN
  • Vehicle logo identification method fusing sliding window and Faster R-CNN
  • Vehicle logo identification method fusing sliding window and Faster R-CNN

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Embodiment Construction

[0083] A kind of vehicle mark localization and recognition method based on Faster R-CNN convolution neural network will be elaborated below in conjunction with 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.

[0084] The concrete process of a kind of vehicle logo localization and recognition method based on Faster R-CNN convolutional neural network of the present invention is as follows figure 1 As shown, the specific steps are as follows:

[0085] Step 1: Define the set of car logo types as C={C i |i=1,...,t}, where t is the total number of vehicle logos, and a corresponding data set containing ground truth is established. In this embodiment, t is 10, and C={C i | i =1,2,...,t}=

[0086] {audi, bmw, benz, cadillac, chevloret, jord, volks, hyundai, mitsubishi, volvo};

[0087] Step 2: Construct a convolutional neural network with 10 layers. The 10 layers are c...

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Abstract

The invention discloses a vehicle logo locating and identification method fusing a sliding window and a Faster R-CNN. A computer vision technology is used; a vehicle logo is roughly located by identifying a vehicle lamp to cope with the situations that a license plate of a vehicle is shielded and the vehicle does not have the license plate; the vehicle logo identification problem is solved based on the CNN; and positive and negative samples are dynamically generated through RPN, so that the input samples are different, the over-fitting degree of the network is reduced, the robustness of the network is improved, a conventional working mode of identifying the vehicle by the license plate is improved, reliable help is provided for fighting illegal criminal behaviors such as cloned vehicle license plates, one vehicle with multiple license plates, false license plates and the like, the reliability of intelligent traffic is further improved, and a large amount of manpower costs are reduced.

Description

technical field [0001] The invention belongs to the field of computer vision technology and image processing technology, and in particular relates to a vehicle logo positioning and recognition method, specifically a vehicle logo positioning and recognition method that integrates sliding windows and Faster R-CNN convolutional neural networks. Background technique [0002] Since the 20th century, the economies of all countries in the world have been developing continuously, and the types and quantities of automobiles have also increased. As a convenient means of transportation and transportation, automobiles are closely related to the lives of modern humans. While vehicles provide people with convenient life, their parking and supervision have also become an urgent problem to be solved. Therefore, the traditional road monitoring method based on human eye recognition cannot meet the requirements. Modern intelligent traffic control systems have become the future of global roads....

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06N3/04
CPCG06N3/045G06F18/25G06F18/214
Inventor 高飞汪韬刘浩然卢书芳毛家发肖刚
Owner ZHEJIANG UNIV OF TECH
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