Abstract
High-accuracy image matching algorithms are a crucial step of 3D reconstruction from multiple images, which can be used to create the accurate 3D models of spatial entities. SURF, a conventional image matching algorithm, has the disadvantages of sparse matching, high incorrect rate. Thus, SURF matching algorithms are hard to meet the demand of high-accuracy 3D reconstruction. This paper introduces the MSURF, a new image matching algorithm which combines homography and SURF algorithm. Experiments are performed by comparing MSURF with conventional matching algorithms from the aspects of quantity and quality, and the experimental results verifies that MSURF can not only increase the quantity of match points, but also improve the accuracy of match points. In addition, the paper analyzes the experimental result, and acquired the application features of MSURF. Thereby, the new proposed matching algorithm, MSURF, extends and improves the existing matching algorithm, and ensures the high-accuracy 3D reconstruction.
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