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The Image Matching Algorithm Basing on Homographic Constraints for Marine Surveying, Mapping and 3D Reconstruction

ABSTRACT Chen, Y.; Le, Y.; Xie, Z.; Qiu, Z; Zhang, C.; Cao, B., and Fang, S., 2019. The image matching algorithm basing on homographic constraints for marine surveying, mapping and 3D reconstruction. In: Hoang, A.T. and Aqeel Ashraf, M. (eds.), Research, Monitoring, and Engineering of Coastal, Port, and Marine Systems. Journal of Coastal Research, Special Issue No. 97, pp. 184–190. In the marine surveying and mapping, high-accuracy image matching is of crucial importance to improve the surveying and mapping accuracy. For the low texture area, coastal zone, island and reef, the accuracy of the mapping and 3D reconstruction would be impacted by the number of matching points and the matching accuracy, using the conventional matching algorithms basing on the imaging feature, such as scale-invariant feature transform (SIFT), speed-up robust features (SURF) and oriented brief (ORB) et al.. To overcome and reduce the problem, this paper proposes a new image matching algorithm, the homographic constraint SURF algorithm, which combines the homographic constraint condition and SURF algorithm in order to increase the number of the high-accuracy matching points and improve the accuracy of the mapping and 3D reconstruction for the marine surveying and mapping. Through experiments performance, HCSURF can extract the more number of the matching points and obtain the higher matching accuracy for island and reef images, comparing with the SIFT, SURF and ORB algorithms. In addition, the characteristics and application categories of the HCSURF are analyzed and discussed basing on the experimental results. Using the new proposed matching algorithm can improve and ensure the accuracy of the marine surveying, mapping and 3D reconstruction.