Vehicle driving lane positioning method based on semantic segmentation

A vehicle driving and positioning method technology, which is applied in the field of computer vision, can solve the problems of no lane segmentation, poor robustness, and high threshold requirements, and achieve convenient and accurate vehicle positioning, low memory requirements, and few training parameters.

Inactive Publication Date: 2018-11-06
FUZHOU UNIVERSITY
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AI Technical Summary

Problems solved by technology

[0004] At present, the commonly used lane line detection based on Hough transform has poor anti-interference, and the complex environment may lead to excessive calculation; lane line detection based on threshold segmentation requires a high threshold for judgment; lane line de

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  • Vehicle driving lane positioning method based on semantic segmentation
  • Vehicle driving lane positioning method based on semantic segmentation
  • Vehicle driving lane positioning method based on semantic segmentation

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Embodiment Construction

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

[0033] Such as figure 1 As shown, a vehicle lane location method based on semantic segmentation includes the following steps: Step S1: Acquire road images;

[0034] Step S2: Construct a two-lane semantic segmentation network based on the Segnet network, perform feature extraction on the road image, output the lane segmentation mask map of the road image, and determine whether each pixel on the road image belongs to the left lane, right lane or non-lane;

[0035] Step S3: Carry out target detection on the vehicle in the road image, obtain the location of the vehicle on the road image, and output the coordinates of the vehicle in the road image;

[0036] Step S4: Fusion of the lane segmentation mask map and vehicle target detection results to determine the lane where the vehicle is located.

[0037] In this embodiment, the picture part is first input, w...

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Abstract

The invention discloses a vehicle driving lane positioning method based on semantic segmentation. The method comprises the steps of firstly, constructing a double-lane semantic segmentation network onthe basis of a Segnet network after a road image is acquired; performing feature extraction on the road image; outputting a lane segmentation mask image of the road image; judging whether each pixelpoint on the road image belongs to a left lane, a right lane or a non-lane; carrying out target detection on a vehicle in the road image; acquiring the position of the vehicle on the road image; and finally, by fusing the lane segmentation mask image and a vehicle target detection result, judging the lane where the vehicle is located. According to the method, an encoder-decoder architecture network is adopted to realize end-to-end training of a double-lane semantic segmentation model; and the requirement of detection timeliness is met.

Description

technical field [0001] The invention relates to the technical field of computer vision, in particular to a vehicle lane positioning method based on semantic segmentation. Background technique [0002] Visual perception plays a key role in the development of assisted driving systems in vehicles. In the vehicle assisted driving system, image processing and computer vision technology are used to ensure a safe distance between vehicles and the correct lane, and to respond and deal with some abnormal conditions in a timely manner. Detect and segment lanes and vehicles, and locate the lane in which the vehicle is driving to assist vehicle driving. [0003] Most of the traditional vehicle lane location methods are realized by lane line detection. The lane line is detected, and the vehicle driving lane is located according to the position of the lane line. Some current technical solutions are: lane line detection based on Hough transform, using the characteristic that the road ed...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/46G06N3/04G06T7/11
CPCG06T7/11G06V20/588G06V10/44G06N3/045
Inventor 黄立勤裴晨皓
Owner FUZHOU UNIVERSITY
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