A RANSAC-ST method for image matching

Fengman Jia; Zhizhong Kang

doi:10.1117/12.2234742

2 March 2016 A RANSAC-ST method for image matching

Fengman Jia, Zhizhong Kang

Proceedings Volume 9901, 2nd ISPRS International Conference on Computer Vision in Remote Sensing (CVRS 2015); 990115 (2016) https://doi.org/10.1117/12.2234742
Event: 2015 ISPRS International Conference on Computer Vision in Remote Sensing, 2015, Xiamen, China

Abstract

Facing challenges of external environmental noise, it is necessary to find a robust, accurate and fast image-matching method. This paper proposed a method combining SIFT (Scale Invariant Feature Transform) algorithm and RANSACST (RANdom Sampling Consensus with Statistical Testing). RANSAC-ST algorithm is the improvement of RANSAC, which uses a strategy for best model determination in terms of the statistical characteristics of a deterministic mathematical model for hypothesis testing. It will generate a statistical histogram of all hypothesis fundamental matrices, and then the fundamental matrix whose convergence degree reaches the threshold is regarded as the best model. Experimental results show that with the proposed algorithm, the robustness and computation efficiency of correspondence matching can be effectively improved.

Citation Download Citation

Fengman Jia and Zhizhong Kang "A RANSAC-ST method for image matching", Proc. SPIE 9901, 2nd ISPRS International Conference on Computer Vision in Remote Sensing (CVRS 2015), 990115 (2 March 2016); https://doi.org/10.1117/12.2234742

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