Structured output method of preceding vehicle information based on cascaded convolutional neural network

A convolutional neural network and vehicle information technology, which is applied in the field of vehicle information structured output, can solve the problems of long positioning time, low recognition rate, and high resolution requirements of the image to be detected, so as to improve the accuracy and reduce the detection efficiency. area, the effect of speeding up detection and recognition

Active Publication Date: 2018-04-17
XIDIAN UNIV
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Problems solved by technology

The disadvantage is that the resolution of the image to be detected is high, the positioning time is long, and the recognition rate is not high.

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  • Structured output method of preceding vehicle information based on cascaded convolutional neural network
  • Structured output method of preceding vehicle information based on cascaded convolutional neural network
  • Structured output method of preceding vehicle information based on cascaded convolutional neural network

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Embodiment Construction

[0032] The embodiments and effects of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0033] refer to figure 1 , the implementation steps of the present invention are as follows:

[0034] Step 1, get the training sample set:

[0035] (1a) Take videos and pictures of the vehicle in front of you in different scenes, environments, and lighting conditions for a total duration of not less than 10 hours or the final picture is not less than 200,000 pieces, and use these data pictures to form a sample set;

[0036] (1b) Randomly select 5% of the pictures from the sample set, mark the area of ​​the car body, the area of ​​the license plate, the area of ​​the car logo and the category of the car logo in each selected picture, as the initial sample set;

[0037] figure 2 The partial positive sample image of the car body training sample is given, image 3 The partial positive sample image of the license plate training sample i...

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Abstract

The present invention proposes a method for structured output of preceding vehicle information based on a cascaded convolutional neural network, which mainly solves the problem that existing methods cannot quickly detect and recognize vehicle bodies, license plates, and vehicle logos at one time in complex environments. The implementation process is: 1. Obtain the sample set, and select the initial sample set of the car body; 2. Use the binary norm gradient method to train the initial sample set of the car body; 3. Train the car body, license plate, and car body respectively. Target convolutional neural network; 4. Judging the car body area and color according to the trained car body convolutional neural network; 5. Judging the license plate area and identifying the license plate number according to the trained license plate convolutional neural network; 6. According to the training A good car logo convolutional neural network can judge the area and category of the car logo; 7. Output all the obtained information to the frame image. The invention can more accurately detect and identify the vehicle information in front in a complex environment, and can be used for intelligent monitoring, intelligent traffic, driver assistance and traffic information detection.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a method for structured output of vehicle information, which can be used for intelligent monitoring, intelligent transportation, driver assistance systems and traffic information detection. Background technique [0002] Vehicle detection and recognition in computer vision refers to obtaining vehicle information only by using the image input of the camera, which is a technology with very broad application prospects. The vehicle detection system based on computer vision has low hardware cost and can perceive rich environmental information, but it is greatly affected by environmental changes and is sensitive to changes in lighting conditions. Vehicle information detection and recognition has good application prospects in many fields, but due to the diversity of vehicles, background clutter, weather effects, lighting conditions, self-occlusion and other factors, ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06K9/62G06K9/66
CPCG06V20/584G06V30/194G06V2201/08G06F18/2411
Inventor 韩红徐志敏王伟张鼎
Owner XIDIAN UNIV
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