Novel image matching confidence fusion evaluation algorithm based on support vector machine

Lamei Zou; Zhiguo Cao; Tianxu Zhang

doi:10.1117/12.749436

15 November 2007 Novel image matching confidence fusion evaluation algorithm based on support vector machine

Lamei Zou, Zhiguo Cao, Tianxu Zhang

Proceedings Volume 6788, MIPPR 2007: Pattern Recognition and Computer Vision; 67881D (2007) https://doi.org/10.1117/12.749436
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

Confidence evaluation is an important technique in image matching process. This paper proposes a confidence level evaluation method for image matching result based on support vector machine (SVM). We divide the matching result into two different types: the correct result and the wrong result. So we translate the match result's confidence evaluation problem into the matching result's classification. This paper firstly provides a method of how to prepare the character parameters which can accurately reflect the matching performance. And then the SVM based on Gaussian kernel is used as a classifier to classify the match result and discriminate the match result's type. The experiments show that this method is effective. Compared with the Dempster-Shafer (D-S) evidence reasoning fusion method it has much higher accuracy.

Citation Download Citation

Lamei Zou, Zhiguo Cao, and Tianxu Zhang "Novel image matching confidence fusion evaluation algorithm based on support vector machine", Proc. SPIE 6788, MIPPR 2007: Pattern Recognition and Computer Vision, 67881D (15 November 2007); https://doi.org/10.1117/12.749436

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