A Part Image Mosaic Method Based on Sparse Feature Points

doi:10.3969/j.issn.1006-2475.2019.02.004

Abstract

Abstract: Aiming at the poor results that many image mosaic methods based on the feature points are used to parts image with weak texture, few features and many similar regions, an improved method is proposed. Firstly, the feature points are extracted by the FAST method, and the candidate points sets for matching are generated from them. Secondly, the gray feature values are sampled by template region, and the points matching results are obtained via setting the rotation angle and scaling search regions with the structural similarity index measurement (SSIM) method. Finally, the rotation, scaling, translation parameters are worked out by the points matching results. The last results of the parameters are gained through 3σ principle removing abnormal values. The experiment results show that the new method could get good rotation, scaling, translation parameters and mosaic image when angle search region is［-45°,+45°］ and scaling search region is［0.5,1.5］.

Key words: image mosaic, FAST feature points, feature points matching, structural similarity index measurement (SSIM)

CLC Number:

TP391

ZHANG Qin1,2, JIA Yuan1, WANG Yao-bin1. A Part Image Mosaic Method Based on Sparse Feature Points[J]. Computer and Modernization, 2019, 0(02): 19-.

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