نتایج جستجو برای: scale matching
تعداد نتایج: 670977 فیلتر نتایج به سال:
Abstract Object matching is a key technology for map conflation, data updating, and quality assessment. This article proposed new Voronoi diagram-based approach multi-scale road networks (VAMRN). Using this method, we first created diagrams of the network using strategy discretizing lines into points adding dense to special intersection segments. Then, used diagram segment find candidates. Fina...
Reliable feature matching plays an important role in the fields of computer vision and photogrammetry. Due to complex transformation model caused by photometric geometric deformations, limited discriminative power local descriptors, initial matches with high outlier ratios cannot be addressed very well. This study proposes a reliable outlier-removal algorithm combining two affine-invariant cons...
We approach the problem of 2-D and 3-D puzzle solving by matching the geometric features of puzzle pieces three at a time. First, we define an affinity measure for a pair of pieces in two stages, one based on a coarse-scale representation of curves and one based on a fine-scale elastic curve matching method. This re-examination of the top coarse-scale matches at the fine scale results in an opt...
Least square matching (LSM) is one of the most accurate image matching methods in photogrammetry and remote sensing. The main disadvantage of the LSM is its high computational complexity due to large size of observation equations. To address this problem, in this paper a novel method, called fast least square matching (FLSM) is being presented. The main idea of the proposed FLSM is decreasing t...
Scene matching is used for image registration in many fields. There are usually translation and an arbitrary unknown rotation angle between reference and template images. The corresponding scene matching algorithm costs far more computing time than that with small rotation angle and translation. Conceptions of generalized vector image, gray-scale image rotation transformation, gray-scale image ...
We use a conventional matching criterion, the sums of squares of differences, SSD, which is statistically meaningful when ergodicity of its matching regions is assumed. Here, simple statistical similarity measures are applied to the scale tree to simplify it into a set of relatively homogeneous regions. This simplified scale tree is then used to generate matching regions which frequently satisf...
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