Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-06-19 Cooperative journals: 《计算机应用研究》
Abstract： To improve the robustness of the existing multi-spectral image registration algorithms, this paper proposed a new algorithm based on multi-scale support region descriptors. Firstly, the algorithm extracted the Harris corner points as feature points. Secondly, it constructed the descriptor by combining the edge direction histograms calculated respectively in the support regions of different sizes around a feature point. Then, the similarity criterion was the Euclidean distance, and it obtained the initial matches by the ratio method. Finally, this paper proposed an outlier removal algorithm based on RANSAC algorithm. The experimental results show that the proposed algorithm can match multi-spectral images effectively, be more robust than the existing algorithms, and obtain more matches that are correct.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-04-19 Cooperative journals: 《计算机应用研究》
Abstract： Quasi-dense matching is widely used in multi-view 3D reconstruction, and it is important for reconstruction results. Aiming at the quasi-dense matches diffused by the seed points extracted from Sift algorithm are less accurate, this paper proposed a quasi-dense matching algorithm based on scale invariant Harris corners. Firstly, it structured the scale invariant Harris features in multi-scale space, and the feature sets between different views are bidirectional matched by cosine distance similarity measure; Then the seeds selected from the initial matches are applied in quasi-dense matching algorithms by best and first propagation strategy; Finally, a local non-maximum suppression strategy is applied to resampling the quasi-dense matches. Experiments show that the seeds extracted by this algorithm can not only reflect the scene structure information, but also have scale invariant characteristics. And for quasi-dense diffusion, the matching effect and accuracy can be improved, and it is an effective quasi-dense matching algorithm for 3D reconstruction.
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