局部特征点对称约束的图像拼接增强方法

doi:10.7527/S1000-6893.2022.26948

Abstract

Abstract: In this paper， an image mosaic enhancement method with symmetrical constraint of local feature points is proposed. Firstly， according to the internal and external parameter matrix of the camera， the forward local constraint region of the feature points is calculated， and the set of positive matching points is obtained. Then， the inverse local constraint region is calculated， and the set of inverse matching points is obtained. The intersection in the set of forward and reverse matching point pairs is found， and the final correct matching point pair set which satisfies the symmetric constraint condition is obtained. Combining this enhancement method with the existing advanced stitching model learning algorithm， the optimal image transformation is obtained， and finally the stitched image is obtained according to the image transformation model. This method effectively overcomes the problem that the threshold of the RANSAC algorithm needs to be manually adjusted when learning different models， thus reducing the parameter sensitivity of the algorithm， and improving the image stitching accuracy. Experiments show that our method is superior to existing methods both qualitatively and quantitatively.

Key words: computer vision, image stitching, local constraint, internal parameter matrix, feature point matching

CLC Number:

V243
TP391

ZHONG Mengfan, PEI Jihong. Image stitching enhancement method with symmetrical constraint of local feature points[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(S1): 726948-726948.

References

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Image stitching enhancement method with symmetrical constraint of local feature points

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