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Indoor Scene Splicing Based on Genetic Algorithm and ORB

Tao Zhang1,*, Yi Cao2

1 School of Mechanical Engineering, North China University of Water Conservancy and Hydroelectric Power, Zhengzhou, 450045, China
2 Department of Electrical and Computer Engineering, University of Windsor, Windsor, ON, 9B 3P4, Canada

* Corresponding Author: Tao Zhang. Email: email

Intelligent Automation & Soft Computing 2022, 33(3), 1677-1685. https://doi.org/10.32604/iasc.2022.027082

Abstract

The images generated by the image stitching algorithm have false shadow and poor real-time performance, and are difficult to maintain visual consistency. For this reason, a panoramic image stitching algorithm based on genetic algorithm is proposed. First, the oriented fast and rotated brief (ORB) algorithm is used to quickly perform detection and description of feature, then the initial feature point pairs are extracted according to the Euclidean distance for feature point rough matching, the parallelism of genetic algorithm is used to optimize the feature point matching performance. Finally, the PROSAC algorithm is used to remove mismatched point pairs and get the transformation matrix to complete the image stitching.

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Cite This Article

T. Zhang and Y. Cao, "Indoor scene splicing based on genetic algorithm and orb," Intelligent Automation & Soft Computing, vol. 33, no.3, pp. 1677–1685, 2022.



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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