Binocular vision-based method and apparatus for detecting barrier in indoor shadow environment

An obstacle detection and binocular vision technology, applied in the field of computer vision, can solve problems such as large amount of calculation, large error and redundant information, and inability to accurately extract obstacles, and achieve accurate, fast and accurate parallax calculation methods. Accurately obtained effect

Active Publication Date: 2017-05-10
SOUTH CHINA UNIV OF TECH
View PDF3 Cites 12 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, due to uneven illumination and object occlusion, shadows will be generated around obstacles, which will affect the extraction of obstacle contours and subsequent measurement work.
The traditional shadow elimination algorithm reduces the gray level difference between the ground and obstacles when eliminating shadows, so that subsequent obstacles cannot be accurately extracted, and the algorithm parameters need to be manually set and lack of adaptability to the environment
The disparity calculation method based on dense matching has a large amount of calculation and large errors and redundant information when measuring obstacles, which cannot meet the real-time and accuracy requirements

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
  • Binocular vision-based method and apparatus for detecting barrier in indoor shadow environment
  • Binocular vision-based method and apparatus for detecting barrier in indoor shadow environment
  • Binocular vision-based method and apparatus for detecting barrier in indoor shadow environment

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0024] The present invention is based on a binocular vision-based obstacle detection method in an indoor shadow environment. A binocular vision system is used to detect ground obstacles in an indoor shadow environment. The specific implementation steps are as follows:

[0025] Such as figure 1 As shown, a method for detecting obstacles in an indoor shadow environment based on binocular vision, using a binocular vision system, includes steps:

[0026] (1) Eliminate shadows through the single-scale Retinex algorithm, extract the color saturation of the original image, and fuse it with the image information that eliminates shadows. Adaptively adjust and enhance the gray level difference between the ground and obstacles through the ambient brightness information to distinguish obstacles come out;

[0027] (2) Use the seed filling algorithm to fill the ground area of ​​the fused image, and then obtain the obstacle area through threshold segmentation, erosion, and expansion operati...

Embodiment 2

[0046] A binocular vision-based obstacle detection device in an indoor shadow environment, using a binocular vision system, including:

[0047] The shadow elimination module is used to eliminate shadows through the single-scale Retinex algorithm, extract the color saturation of the original image, and fuse it with the image information for shadow elimination. Adaptively adjust and enhance the gray level difference between the ground and obstacles through the ambient brightness information, and Obstacles are distinguished;

[0048] The obstacle detection module is used to use the seed filling algorithm to fill the ground area of ​​the fused image, and then obtain the obstacle area through threshold segmentation, erosion, and expansion operations, and obtain its circumscribed rectangle;

[0049] The obstacle measurement module is used to use the binocular vision system to use the obtained obstacle area as a template to match and calculate the parallax of the center point in the ...

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 a binocular vision-based method for detecting a barrier in an indoor shadow environment. A binocular vision system is adopted. The method comprises the steps of (1) removing a shadow, extracting color saturation of an original image, performing fusion with image information subjected to shadow removal, and adaptively adjusting and increasing grayscale difference of the ground and the barrier through environmental brightness information; (2) filling a ground region of a fused image by utilizing a seed filling algorithm, and obtaining a barrier region through threshold segmentation, corrosion and expansion operations; and (3) performing matching in a right camera image by taking the obtained barrier region as a template through applying the binocular vision system to calculate parallax of a central point, and calculating three-dimensional coordinates of the central point and the width and distance of the barrier. The invention furthermore discloses a binocular vision-based apparatus for detecting the barrier in the indoor shadow environment. According to the method and the apparatus, the barrier can be completely extracted in the indoor shadow environment; and the method and the apparatus are simple and efficient, have relatively good real-time property and relatively high precision, and are suitable for mobile robot navigation and barrier avoidance.

Description

technical field [0001] The invention belongs to the field of computer vision, mainly relates to obstacle detection and binocular measurement, in particular to a method and device for detecting obstacles in an indoor shadow environment based on binocular vision. Background technique [0002] In recent years, with the development of computer and robot technology, machine vision has been widely used in intelligent manufacturing, artificial intelligence and industrial production. The autonomous navigation of mobile robots based on visual guidance has become a hot research topic, and the detection and measurement of ground obstacles is the key and basis for autonomous navigation and obstacle avoidance of robots. However, due to uneven illumination and object occlusion, shadows will be generated around obstacles, which will affect the extraction of obstacle contours and subsequent measurement work. The traditional shadow elimination algorithm reduces the gray level difference bet...

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): G06K9/00G01B11/02G01C3/00
CPCG01B11/02G01C3/00G06V20/20
Inventor 翟敬梅刘坤
Owner SOUTH CHINA UNIV OF TECH
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