Abstract
Symmetric-SIFT is an effective technique used for registering multimodal images. It is based on a well-known image registration technique named Scale Invariant Feature Transform (SIFT). Similar to SIFT, Symmetric-SIFT detects many stable keypoints even though not all of which are useful. Experiments show that matching keypoints are mostly on or near the edge. Based on the phenomenon, we propose an effective method. In our method, We extract the edge and classify keypoints by whether they are on the edge or not. Then we delete the points that are far from the edge and match the remained ones. Finally, we get the matching set after filtering the initial matching result with the threshold value got by the Bayesian formula. The experimental results show that the proposed method can not only greatly reduce the matching time, but also effectively improve the matching rate.
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Acknowledgments
This research was supported by “National Natural Science Foundation of China” (No.61272523) and “the National Key Project of Science and Technology of China” (No.2011ZX05039-003-4).
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Zhao, D., Wang, Q., Sun, H., Hu, X. (2013). A Method of Acceleration Applied in Symmetric-SIFT and SIFT. In: Sun, Z., Deng, Z. (eds) Proceedings of 2013 Chinese Intelligent Automation Conference. Lecture Notes in Electrical Engineering, vol 256. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38466-0_64
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DOI: https://doi.org/10.1007/978-3-642-38466-0_64
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