The effect of rainfall on feature points extraction and image stitching
Abstract
The aim of this paper is to investigate the effects of rainfall on image stitching by measuring the performance of the Harris corner detector, Scale-Invariant Feature Transform (SIFT) detector, and the Speeded Up Robust Feature (SURF) detector. A set of images were captured by using two cameras during light rain and during heavy rain. The number of detected features points was used as the performance measure. The results indicate that all the detectors are capable to extract a substantial amount of feature points. However, the rainfall does reduce the number of detected feature points by 48 and 67% when the Harris corner detector and the SURF detector were adopted respectively. At the end, the images were stitched together based on the feature points extracted by using the Harris corner detector. The results indicate that the effect of rainfall is negligible as long as there is a substantial amount of distinctive feature points.
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Chia et al. [4] observed that the number of feature points extracted by Harris and SURF detectors was reduced by 48% and 68%, respectively due to falling rain.
“Chia et al. [4] observed that the number of feature points extracted by Harris and SURF detectors was reduced by 48% and 68%, respectively due to falling rain.”
From A Review of Detection and Removal of Raindrops in Automotive Vision Systems (2021) · cites this paper as [4]
Cites
Distinctive Image Features from Scale-Invariant Keypoints
Lowe, D. G. (2004) · International Journal of Computer Vision · doi:10.1023/b:visi.0000029664.99615.94 · Cited by 55,589 · see citing works
Fischler, M. A., & Bolles, R. C. (1981) · Communications of the ACM · doi:10.1145/358669.358692 · Cited by 25,893 · see citing works
SURF: Speeded Up Robust Features
Bay, H., Tuytelaars, T., & Van Gool, L. (2006) · Lecture Notes in Computer Science · doi:10.1007/11744023_32 · Cited by 14,955 · cited 1× · see citing works
“This includes the Harris corner detector [1], the ShiftInvariant Feature Transform (SIFT) detector [2], and the Speeded-Up Robust Feature (SURF) detector [3].”
MethodSpeeded-Up Robust Features (SURF)
Bay, H., Ess, A., Tuytelaars, T., & Van Gool, L. (2008) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2007.09.014 · Cited by 13,557 · see citing works
A Combined Corner and Edge Detector
Harris, C., & Stephens, M. (1988) · Procedings of the Alvey Vision Conference 1988 · doi:10.5244/c.2.23 · Cited by 12,901 · see citing works
Vedaldi, A., & Fulkerson, B. (2010) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/1873951.1874249 · Cited by 2,675 · see citing works
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A Review of Detection and Removal of Raindrops in Automotive Vision Systems
Hamzeh, Y., & Rawashdeh, S. A. (2021) · Journal of Imaging · doi:10.3390/jimaging7030052 · Cited by 21 · see citing works
“[4] observed that the number of feature points extracted by Harris and SURF detectors was reduced by 48% and 68%, respectively due to falling rain.”
Method
- Authors
- Chia, W. C., Yeong, L. S., Ch'ng, S. I., Seng, K. P., & Ang, L.-M.
- Affiliations
- Sunway University (MY)
- Edith Cowan University (AU)
- Venue
- 2014 International Conference on Information Science, Electronics and Electrical Engineering
- Publisher
- IEEE
- Published
- 2014-04
- Pages
- 1382-1386
- OpenAlex
- W2078305342
- Cited by
- 7
- References
- 6
- Citations by year
- 2025: 2 · 2023: 1 · 2021: 1 · 2020: 1 · 2019: 1 · 2018: 1
- FWCI
- 0.00
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- International Conference on Information Science, Electronics and Electrical Engineering (publishedVersion)
- Research Online (Edith Cowan University) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Image and Video Retrieval Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Vision and Imaging
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image and Video Stabilization
- Keywords
- rainfall, image stitching, feature point extraction, Harris corner detector, SIFT, SURF, stereo vision
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