ITM Web Conf.
Volume 47, 20222022 2nd International Conference on Computer, Communication, Control, Automation and Robotics (CCCAR2022)
|Number of page(s)||6|
|Section||Algorithm Optimization and Application|
|Published online||23 June 2022|
Research on robot scene recognition based on improved feature point matching algorithm
College of Mechanical and Electronic Engineering, Qingdao University of Science and Technology, Qingdao, China
* Corresponding author: firstname.lastname@example.org
A new feature description method based on the fusion of fast retina keypoint (FREAK) and the rotation-aware binary robust independent elementary features (rRBRIEF) is proposed to realize the effective combination of efficiency and accuracy of the two feature descriptions. In addition, in the elimination stage of mismatched point pairs, by setting the base point and its neighborhood, an improved neighborhood parallel random sample consensus (RANSAC) algorithm is proposed to achieve efficient parallel operation of the algorithm in multiple local neighborhoods. The improved feature point matching algorithm and the existing algorithm were tested in different scales, different rotations, different illuminations, and different fuzzy data sets. The experimental results show that the improved algorithm improves the average scene recognition accuracy by 18.21%, improves the efficiency by 15.58%, and shows good robustness.
Key words: Scene recognition / Feature point matching / Feature description / Random sample consensus algorithm
© The Authors, published by EDP Sciences, 2022
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