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 Yan Lin and Bo Liu.Underwater Image Bidirectional Matching for Localization Based on SIFT[J].Journal of Marine Science and Application,2014,(2):225-229.[doi:10.1007/s11804-014-1252-z]
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Underwater Image Bidirectional Matching for Localization Based on SIFT


Underwater Image Bidirectional Matching for Localization Based on SIFT
Yan Lin and Bo Liu
Yan Lin and Bo Liu
1. State Key Laboratory of Structural Analysis for Industrial Equipment, Dalian University of Technology, Dalian 116024, China 2. Department of Naval Architecture and Ocean Engineering, Dalian University of Technology, Dalian 116024, China
SWATH underwater image registration SIFT bidirectional matching strategy automatic stitching
For the purpose of identifying the stern of the SWATH (Small Waterplane Area Twin Hull) availably and perfecting the detection technique of the SWATH ship’s performance, this paper presents a novel bidirectional image registration strategy and mosaicing technique based on the scale invariant feature transform (SIFT) algorithm. The proposed method can help us observe the stern with a great visual angle for analyzing the performance of the control fins of the SWATH. SIFT is one of the most effective local features of the scale, rotation and illumination invariant. However, there are a few false match rates in this algorithm. In terms of underwater machine vision, only by acquiring an accurate match rate can we find an underwater robot rapidly and identify the location of the object. Therefore, firstly, the selection of the match ratio principle is put forward in this paper; secondly, some advantages of the bidirectional registration algorithm are concluded by analyzing the characteristics of the unidirectional matching method. Finally, an automatic underwater image splicing method is proposed on the basis of fixed dimension, and then the edge of the image’s overlapping section is merged by the principal components analysis algorithm. The experimental results achieve a better registration and smooth mosaicing effect, demonstrating that the proposed method is effective.


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Supported by the “Liaoning Baiqianwan” Talents Program (No. 200718625), the Program of Scientific Research Project of Liao Ning Province Education Commission (No. LS2010046), and the National Commonweal Industry Scientific Research Project (No. 201003024).
Last Update: 2014-06-10