Outdoor parking lot non-occupied parking stall identification method based on aerial photography images

An aerial image and recognition method technology, applied in the field of image processing, can solve problems such as complex methods, and achieve the effects of wide detection range, improved recognition accuracy, and strong mobility

Active Publication Date: 2015-12-16
BEIHANG UNIV
View PDF5 Cites 28 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

There are many methods for detecting the occupancy of parking spaces based on video. The detection method is to use the camera to collect images, and use computer image processing and pattern recognition technology to process the continuous images, so as to achieve the purpose of detecting whether the parking spaces are parked. The method requires detecting the occupancy of the vehicle in the parking space while detecting the parking space, which is more complicated than the method of directly detecting vacant parking spaces

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Outdoor parking lot non-occupied parking stall identification method based on aerial photography images
  • Outdoor parking lot non-occupied parking stall identification method based on aerial photography images
  • Outdoor parking lot non-occupied parking stall identification method based on aerial photography images

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0019] The present invention will be described in detail below in conjunction with the accompanying drawings and embodiments.

[0020] The invention provides a method for identifying a vacant parking space in an outdoor parking lot based on an aerial image. The identification method first extracts the ROI area of ​​the vacant parking space, and converts the image of the area into a pointer image for storage as a template image; then according to the template image Multi-template matching is performed on the aerial images to identify the vacant parking spaces in each frame of aerial images; according to the identified vacant parking spaces, the vehicle layout in the parking lot area is calculated to obtain the type of parking spaces in the parking lot; Identify vacant parking spaces at all positions within the panoramic range to determine the overall area of ​​the parking lot; adjust the size of the matching template image through the linear change relationship between the aeria...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses an outdoor parking lot non-occupied parking stall identification method based on aerial photography images. The identification method includes the steps of template extraction based on an ROI area; parking stall identification based on template matching; parking stall structural determination based on the identified non-occupied parking stall spatial distribution; and dimension adjustment of the parking stall template based on the aerial photography height. The unmanned plane aerial photography images have the advantages of wide visual field and high mobility. With respect to a non-occupied parking stall detection method, unmanned planes fly over a plurality of parking lots in a short time to obtain multi-area non-occupied parking stall information, so that the parking lot non-occupied parking stall detection method based on unmanned plane low-altitude aerial photography images has the advantages of wide detection scope and fast updating speed.

Description

technical field [0001] The invention belongs to the technical field of image processing, and relates to a method for identifying parking spaces within a parking lot based on low-altitude aerial images of unmanned aerial vehicles, in particular to a method for detecting vacant parking spaces in outdoor parking lots based on multi-template matching and the types of parking spaces The identification method also relates to a template size adjustment method based on aerial photography height. technical background [0002] With the rapid development of science and technology, the construction level of transportation facilities in major and medium cities has also been further improved. People's material living standards have also improved, and more and more cars have entered every household. Although urban roads are constantly widening, the number of overpasses is also constantly increasing, and the scale of parking lots is also constantly increasing, it still cannot alleviate the...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00
CPCG06V20/13
Inventor 王云鹏周思达余贵珍于海洋孙伟力
Owner BEIHANG UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap