Method for detecting full line of lane based on optical flow point locus statistics

A detection method and technology of optical flow points, applied in computing, computer parts, instruments, etc., can solve the problems of weak robustness, low detection accuracy of lane lines, easy to be affected by road surface, weather and light, etc. Achieve the effect of high detection accuracy and strong robustness

Inactive Publication Date: 2015-10-28
XIAN UNIV OF TECH
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Problems solved by technology

[0004] The purpose of the present invention is to provide a detection method based on the optical flow point trajectory statistics of the solid line of the lane line, which solves the problem that the exi

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  • Method for detecting full line of lane based on optical flow point locus statistics
  • Method for detecting full line of lane based on optical flow point locus statistics
  • Method for detecting full line of lane based on optical flow point locus statistics

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Embodiment Construction

[0017] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0018] The present invention is based on the detection method of the solid line of the lane line based on optical flow point trajectory statistics, and the steps mainly include:

[0019] Step 1: Install the camera above the middle of the one-way road;

[0020] Step 2: Preprocessing the video frame image;

[0021] Step 3: Obtain the set of optical flow points of the moving vehicle;

[0022] Step 4: Use the DBSCAN clustering algorithm to segment the optical flow point set of each moving vehicle, and represent the segmented optical flow point set with a fixed-size rectangular area;

[0023] Step 5: Statistically superimpose the segmented area of ​​each moving vehicle, and binarize the result;

[0024] Step 6: Carry out straight line fitting to the midpoint set of the contour points of the white pixel areas that meet the conditions in the bina...

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Abstract

The invention discloses a method for detecting a full line of a lane based on optical flow point locus statistics. The method comprises the steps of step 1, mounting a camera above the middle part of a one-way road; step 2, performing preprocessing on a video frame image; step 3, acquiring optical flow point sets of moving vehicles; step 4, dividing the optical flow point set of each moving vehicle by means of a DBSCAN clustering algorithm, and representing the divided optical flow point sets by a rectangular area with a fixed size; step 5, performing statistical stacking on the divided area of each moving vehicle, and performing binarization processing on a result; step 6, performing linear fitting on the middle point set of contour points of a white pixel area which accords with a condition in a binary image; and step 7, determining the full line of the lane by means of a line which is obtained through fitting the middle point set. The method provided by the invention is not affected by illumination, weather, vehicle and road condition. Furthermore the method realizes high detection precision for the full line of the lane and high robustness.

Description

technical field [0001] The invention belongs to the technical field of intelligent traffic monitoring, and relates to a detection method of a solid line of a lane line based on optical flow point trajectory statistics. Background technique [0002] Traffic congestion and frequent traffic accidents on urban traffic roads have seriously affected the rapid and healthy development of the economy and the safety of people's lives. The causes of accidents include the problem of compaction lines and compaction lines changing lanes, and based on The detection of traffic violations such as the compaction line of the driving vehicle and the traffic violation of the compaction line changing lanes by computer vision must first detect the solid line of the lane line. [0003] Commonly used computer vision-based lane line detection methods can be divided into two categories, feature-based methods and template-based methods. The former mainly extracts the features of the road in the image,...

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Application Information

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IPC IPC(8): G06K9/00
CPCG06V20/588
Inventor 胡涛李明范彩霞
Owner XIAN UNIV OF TECH
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