Road detection based on superpixels and convolution neural network

A convolutional neural network and road detection technology, which is applied in the field of road detection methods and devices, can solve problems such as poor robustness of road detection, and achieve strong robustness and practicability

Inactive Publication Date: 2017-02-22
TIANJIN POLYTECHNIC UNIV
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Problems solved by technology

[0007] In order to achieve the above purpose, the present invention provides a road detection method based on superpixels and c

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  • Road detection based on superpixels and convolution neural network
  • Road detection based on superpixels and convolution neural network
  • Road detection based on superpixels and convolution neural network

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[0053] In order to enable your examiner to further understand the structure, features and other purposes of the present invention, it is now described in detail in conjunction with the attached preferred embodiments. The illustrated preferred embodiments are only used to illustrate the technical solutions of the present invention, not to limit the present invention. invention.

[0054] figure 1 The overall process according to the invention is given. Such as figure 1 As shown, the road detection method based on superpixels and convolutional neural network according to the present invention includes:

[0055] (1) Use a simple linear iterative clustering algorithm to preprocess the image and divide the image into superpixels of uniform size;

[0056] (2) Using a convolutional neural network to automatically learn features that are most conducive to classification based on superpixel blocks, and train the network;

[0057] (3) Use the trained convolutional neural network to classify r...

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Abstract

The invention provides a road detection method based on superpixels and a convolution neural network, and the method comprises the steps: carrying out the image preprocessing through a simple linear iteration cluster algorithm, and segmenting an image into superpixels which are uniform in size; carrying out the automatic learning of characteristics which facilitate the classification most based on superpixel blocks through employing the convolution neural network, and training the network; carrying out the classification of a road region and a non-road region through employing the trained convolution neural network; and carrying out the optimization of a classification result through a Markov random field according to the relation between the superpixel. Compared with the prior art, the method can effectively detect the road region in a complex environment, and is better in robustness.

Description

technical field [0001] The invention relates to image processing, video monitoring and driving safety, in particular to a road detection method and device. Background technique [0002] Driver assistance systems can reduce the incidence of traffic accidents by giving drivers reminders and guidance. Vision-based road detection is the key to driver assistance systems, it can provide clues for obstacle detection, and it is the basis for scene understanding in driverless driving, which is conducive to path planning. [0003] Generally, roads can be divided into structured roads and unstructured roads. Structured roads refer to roads with obvious road marking lines, clear road boundaries, and special color information, such as expressways, urban roads, etc. The road detection problem can be simplified as road marking line detection. Mature. Unstructured roads refer to roads with a low degree of structure and no clear lane lines and road boundaries. The detection method for uns...

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Application Information

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IPC IPC(8): G06K9/46G06K9/62
CPCG06V10/457G06F18/23G06F18/24
Inventor 耿磊邱玲肖志涛张芳吴骏袁菲
Owner TIANJIN POLYTECHNIC UNIV
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