Abstract
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.
Highlights
AUV (Autonomous Underwater Vehicle) is a type of unmanned underwater vehicle (UUV), Because of its high autonomy, passivity, invisibilityit has been widely used in the field of marine science and military[1]
Many scholars have studied the image matching algorithm based on SURF, Xie Yulai proposed underwater images real-time registration method based on SURF[3]; SU Kexin presented anti-viewpoint changing image matching algorithm based on SURF[4]; Yanwei Pang used fully affine invariant SURF for image matching[5]; ZHAO Lu-lu proposed an images matching algorithm based on SURF and fast approximate nearest neighbor search for that nearest neighbor matching of high-dimensional feature vector was low[6]ˊThe SURF algorithm has achieved good results in a specific application
In the practical application, the traditional SURF algorithm is prone to mismatching, especially in the area where the seabed features are not obvious
Summary
AUV (Autonomous Underwater Vehicle) is a type of unmanned underwater vehicle (UUV), Because of its high autonomy, passivity, invisibilityit has been widely used in the field of marine science and military[1]. Among the image matching algorithms, SURF algorithm as an improved algorithm of the SIFT Accurate extraction of the image feature points is the key to ensure successful matching. In order to reduce the error matching, improve the performance of the SURF algorithm, and ensure the correct matching of the seabed relief image, comprehensively utilize the advantages of SURF algorithm and RANSAC algorithm to present an improved SURF algorithm. The matching image and reference image is preprocessed, use the SURF algorithm to extract their feature points and pre-match, the RANSAC algorithm is used to. Eliminate the mismatching points, and on this basis, the fast and accurate image matching is realized
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