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An image matching optimization algorithm based on pixel shift clustering RANSAC
- Source :
- Information Sciences. 562:452-474
- Publication Year :
- 2021
- Publisher :
- Elsevier BV, 2021.
-
Abstract
- This paper focuses on improving the accuracy of image matching by eliminating the residual mismatches in the matching results of standard RANSAC. Based on pixel shift clustering and RANSAC algorithms, a matching optimization algorithm called pixel shift clustering RANSAC, PSC-RANSAC in short, is proposed in this paper. Firstly, the pixel shift model of space point from two perspectives are established by parallax principle and camera projection model. Then, based on the established pixel shift model, density peaks clustering (DPC) algorithm is used to select the mismatches out to enhance the accuracy of image matching. Meanwhile the comparisons among PSC-RANSAC, standard RANSAC, progressive sample consensus and graph-cut RANSAC show that PSC-RANSAC can more effectively and robustly eliminate the residual mismatches in initial matching results. The proposed method provides an effective tool for optimization on image matching.
- Subjects :
- Matching (statistics)
Information Systems and Management
Computer science
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
02 engineering and technology
RANSAC
Residual
Theoretical Computer Science
Artificial Intelligence
0202 electrical engineering, electronic engineering, information engineering
Point (geometry)
Cluster analysis
Pixel
business.industry
05 social sciences
050301 education
Pattern recognition
Sample (graphics)
Computer Science Applications
Control and Systems Engineering
020201 artificial intelligence & image processing
Artificial intelligence
Parallax
business
0503 education
Software
Subjects
Details
- ISSN :
- 00200255
- Volume :
- 562
- Database :
- OpenAIRE
- Journal :
- Information Sciences
- Accession number :
- edsair.doi...........264bef1e7ba7dbff2a04fb2c0a26fd29