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This paper presents an adaptive redundant keypoint elimination method (RKEM) for the SIFT algorithm to improve image matching performance by dynamically adjusting the threshold value based on image type and distortion. The proposed method enhances the efficiency of RKEM-SIFT by calculating an adaptive threshold that minimizes variance in keypoint distances, leading to better elimination of redundant keypoints. Simulation results demonstrate that the adaptive RKEM outperforms traditional SIFT and other relat

Author

shishpal0666

Language

EN