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Automatic lane line identification method based on low-altitude aerial images

An aerial image and automatic recognition technology, applied in the field of traffic information, can solve problems such as road extraction not involved, and achieve the effects of fast calculation speed, high reliability and simple calculation.

Active Publication Date: 2014-01-08
BEIHANG UNIV
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Problems solved by technology

The existing video processing method for the dynamic camera of low-altitude aircraft is based on the machine learning method to identify the image vehicle, and does not involve road extraction technology

Method used

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  • Automatic lane line identification method based on low-altitude aerial images
  • Automatic lane line identification method based on low-altitude aerial images
  • Automatic lane line identification method based on low-altitude aerial images

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Embodiment Construction

[0039] In order to make the object, technical solution and advantages of the present invention more clear, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments.

[0040] Such as figure 1 Shown is the method for automatic recognition of lane lines based on low-altitude aerial images of the present invention, including steps 1 to 5. Step 1: Use a low-altitude aircraft to collect the original image of the aerial road, and ensure that the shooting angle of the aerial road is in the horizontal direction, and the road area is located in the middle of the image.

[0041] Step 2, preprocessing the collected original image.

[0042] In order to ensure the processing speed, firstly, the width and height are compressed to obtain an image with a width of W and a height of H.

[0043] Then perform grayscale processing, and improve the contrast of the grayscale image, and copy the obtained grayscale image.

[0044] ...

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Abstract

The invention provides an automatic lane line identification method based on low-altitude aerial images. The automatic lane line identification method based on the low-altitude aerial images is applied to the field of intelligent transportation. The automatic lane line identification method based on the low-altitude aerial images comprises the steps that (1) an original image of a road is collected through low-altitude aircrafts, and the situation that the shooting angle of the aerial photography road is in the horizontal direction, and the area of the road is arranged in the middle of the image is ensured; (2) the collected image is converted into a grayscale image, the contrast ratio is improved, the grayscale image is copied, and an edge detection image and a binarization image are obtained according to the grayscale image; (3) connected areas are detected in the edge detection image and the binarization image, and characteristics of the connected areas are recorded; (4) the connected areas are deleted according to the number of pixels of the connected areas, the number of connected boundaries, the size of a bounding rectangle and variance values to obtain a central road line; (5) search is carried out on the two sides of the central road line to find roadside lane lines. The automatic lane line identification method based on the low-altitude aerial images is easy and convenient to calculate, and high in arithmetic speed and reliability, the road portion in an aerial photography video can be effectively extracted, straight roads and curve roads in the aerial images can be detected, and the automatic lane line identification method based on the low-altitude aerial images cannot be disturbed by background changes, and is high in accuracy.

Description

technical field [0001] The invention belongs to the field of traffic information, and relates to a method for automatically recognizing lane lines in low-altitude aerial images in the field of intelligent transportation technology, in particular to a method for identifying and extracting curves in aerial images. Background technique [0002] Due to the dense population in China, the traffic conditions in large and medium-sized cities are becoming more and more congested. Accidents on highways, snow disasters and other special circumstances will lead to traffic paralysis, causing great hidden dangers to driving safety and great inconvenience to citizens' daily travel. At present, traffic state awareness is mainly based on roadbed means, which can only obtain cross-sectional information of discrete point sampling, and it is difficult to obtain continuous and large-scale real-time situation information. Traditional ground traffic command methods cannot cover all road sections an...

Claims

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Application Information

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IPC IPC(8): G06K9/00
Inventor 王云鹏余贵珍郑欣蕊徐永正张毅鹏
Owner BEIHANG UNIV
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