15 November 2007 Novel image matching confidence fusion evaluation algorithm based on support vector machine
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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.
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Lamei Zou, Lamei Zou, Zhiguo Cao, Zhiguo Cao, Tianxu Zhang, 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); doi: 10.1117/12.749436; https://doi.org/10.1117/12.749436
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