ITM Web Conf.
Volume 12, 2017The 4th Annual International Conference on Information Technology and Applications (ITA 2017)
|Number of page(s)||6|
|Section||Session 5: Information Processing Methods and Techniques|
|Published online||05 September 2017|
Improved SURF Algorithm and Its Application in Seabed Relief Image Matching
Department of Automation, School of Power and Mechanical Engineering Wuhan University, Wuhan, China
The matching based on seabed relief image is widely used in underwater relief matching navigation and target recognition, etc. However, being influenced by various factors, some conventional matching algorithms are difficult to obtain an ideal result in the matching of seabed relief image. SURF(Speeded Up Robust Features) algorithm is based on feature points pair to achieve matching, and can get good results in the seabed relief image matching. However, in practical applications, the traditional SURF algorithm is easy to get false matching, especially when the area’s features are similar or not obvious, the problem is more seriously. In order to improve the robustness of the algorithm, this paper proposes an improved matching algorithm, which combines the SURF, and RANSAC (Random Sample Consensus) algorithms. The new algorithm integrates the two algorithms advantages, firstly, the SURF algorithm is applied to detect and extract the feature points then to pre-match. Secondly, RANSAC algorithm is utilized to eliminate mismatching points, and then the accurate matching is accomplished with the correct matching points. The experimental results show that the improved algorithm overcomes the mismatching problem effectively and have better precision and faster speed than the traditional SURF algorithm.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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