Linear protection grid optimized image stitching for mobile robots

Lulu Zhou, Yanling Tian, Gang Lu*, Xiaojun Wu, Qieshi Zhang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Image stitching can be used to in 3D reconstruction to obtain the comprehensive obstacle information, which plays an important role in the field of mobile robots.However, previous algorithms have two problems: 1. The linear structure of the image might have been corrupted. 2. Some inconsistency may exist in the transitional region of the stitched image. In order to solve above problems, in this paper, we propose a grid-based linear structure protection method, which applies the constraints to the lines extracted from the image to protect them from the distortion caused by the mesh deformation process, and resulting in a natural panorama with reduced distortion. This method helps to obtain a natural panoramic image with reduced distortion. At the same time, we use the neighbor weighted based boundary artifact removal approach to process the stitched image, which can avoid the stitching problem and can make the image look more natural. We conducted some experiments, and the results demonstrated that our method is more efficient and more natural as compared with some state-of-the-art methods.

Original languageEnglish
Title of host publication2019 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages661-666
Number of pages6
ISBN (Electronic)9781728137261
DOIs
Publication statusPublished - 2019 Aug
Event2019 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2019 - Irkutsk, Russian Federation
Duration: 2019 Aug 42019 Aug 9

Publication series

Name2019 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2019
Volume2019-August

Conference

Conference2019 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2019
Country/TerritoryRussian Federation
CityIrkutsk
Period19/8/419/8/9

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Control and Optimization

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