Deep-learning-based high-precision traffic sign detection method and system

A traffic sign, deep learning technology, applied in the direction of instruments, character and pattern recognition, computer parts, etc., can solve the problem of low accuracy of traffic signs, improve the accuracy and detection accuracy, improve the accuracy, and increase the proportion Effect

Active Publication Date: 2017-06-30
CHINA UNIV OF PETROLEUM (EAST CHINA)
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Problems solved by technology

[0006] In order to solve the problem of low accuracy of traffic sign detection, the first object of the present invention is to provide a high-precision traffic sign detection method based on deep learning

Method used

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  • Deep-learning-based high-precision traffic sign detection method and system
  • Deep-learning-based high-precision traffic sign detection method and system
  • Deep-learning-based high-precision traffic sign detection method and system

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Embodiment Construction

[0058] It should be pointed out that the following detailed description is exemplary and intended to provide further explanation to the present application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0059] It should be noted that the terminology used here is only for describing specific implementations, and is not intended to limit the exemplary implementations according to the present application. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural, and it should also be understood that when the terms "comprising" and / or "comprising" are used in this specification, they mean There are features, steps, operations, means, components and / or combinations thereof.

[0060] As introduced in the background technology, there is a problem of low accuracy of traffic sign detection ...

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Abstract

The invention discloses a deep-learning-based high-precision traffic sign detection method and system. On the basis of combination of the deep learning technology and the high-precision traffic sign detection technology, training is carried out on an SSD network and a convolution neural network; a traffic sign characteristic after overlapped cutting based on a proportion in a video stream is extracted by using the trained SSD network; according to the traffic sign characteristic extracted by the SSD network, the characteristic of the traffic sign characteristic is extracted by using the trained convolution neural network; and the extracted characteristic of the traffic sign characteristic matches characteristics of positive and negative type traffic signs in a traffic sign image detection database and the positive type traffic signs are kept, thereby obtaining a high-precision traffic sign matching screening result. Therefore, the accuracy rate of the high-precision traffic sign detection can be improved effectively.

Description

technical field [0001] The invention belongs to the field of artificial intelligence, and in particular relates to a high-precision traffic sign detection method and system based on deep learning. Background technique [0002] Deep learning is currently the highest level of machine learning development. As a method of deep learning, convolutional neural network has good results in object recognition, image processing and other fields. For feature extraction, the convolutional neural network has the advantage of automatically learning image features, reducing manual intervention and extracting high-quality features, thus laying a solid foundation for improving the accuracy of image matching. [0003] Since the deep learning method does not do enough targeted detail processing in the image preprocessing module, if the image is too large and the proportion of the target object is too small, the expected high-precision detection results may not be achieved. In order to improve t...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/46
CPCG06V20/582G06V10/443
Inventor 张卫山孙浩云徐亮李忠伟宫文娟
Owner CHINA UNIV OF PETROLEUM (EAST CHINA)
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