ترغب بنشر مسار تعليمي؟ اضغط هنا

A fast point-pattern matching algorithm based on statistical method

105   0   0.0 ( 0 )
 نشر من قبل Zhenjun Zhang
 تاريخ النشر 2019
  مجال البحث فيزياء
والبحث باللغة English




اسأل ChatGPT حول البحث

We propose a new pattern-matching algorithm for matching CCD images to a stellar catalogue based statistical method in this paper. The method of constructing star pairs can greatly reduce the computational complexity compared with the triangle method. We use a subsample of the brightest objects from the image and reference catalogue, and then find a coordinate transformation between the image and reference catalogue based on the statistical information of star pairs. Then all the objects are matched based on the initial plate solution. The matching process can be accomplished in several milliseconds for the observed images taken by Yunnan observatory 1-m telescope.



قيم البحث

اقرأ أيضاً

This paper presents new and efficient algorithms for matching stellar catalogues where the transformation between the coordinate systems of the two catalagoues is unknown and may include shearing. Finding a given object whether a star or asterism fro m the first catalogue in the second is logarithmic in time rather than polynomial, yielding a dramatic speed up relative to a naive implementation. Both acceleration of the matching algorithm and the ability to solve for arbitrary affine transformations not only will allow the registration of stellar catalogues and images that are now impossible to use but also will find applications in machine vision and other imaging applications.
In this paper, we propose and analyze a fast two-point gradient algorithm for solving nonlinear ill-posed problems, which is based on the sequential subspace optimization method. A complete convergence analysis is provided under the classical assumpt ions for iterative regularization methods. The design of the two-point gradient method involves the choices of the combination parameters which is systematically discussed. Furthermore, detailed numerical simulations are presented for inverse potential problem, which exhibit that the proposed method leads to a strongly decrease of the iteration numbers and the overall computational time can be significantly reduced.
Point sets matching method is very important in computer vision, feature extraction, fingerprint matching, motion estimation and so on. This paper proposes a robust point sets matching method. We present an iterative algorithm that is robust to noise case. Firstly, we calculate all transformations between two points. Then similarity matrix are computed to measure the possibility that two transformation are both true. We iteratively update the matching score matrix by using the similarity matrix. By using matching algorithm on graph, we obtain the matching result. Experimental results obtained by our approach show robustness to outlier and jitter.
We present a new and efficient algorithm for finding point sources in the photon event data stream from the Fermi Gamma-Ray Space Telescope, FermiFAST. The key advantage of FermiFAST is that it constructs a catalogue of potential sources very fast by arranging the photon data in a hierarchical data structure. Using this structure FermiFAST rapidly finds the photons that could have originated from a potential gamma-ray source. It calculates a likehihood ratio for the contribution of the potential source using the angular distribution of the photons within the region of interest. It can find within a few minutes the most significant half of the Fermi Third Point Source catalogue (3FGL) with nearly 80% purity from the four years of data used to construct the catalogue. If a higher purity sample is desirable, one can achieve a sample that includes the most significant third of the Fermi 3FGL with only five percent of the sources unassociated with Fermi sources. Outside the galaxy plane, all but eight of the 580 FermiFAST detections are associated with 3FGL sources. And of these eight, six yield significant detections of greater than five sigma when a further binned likelihood analysis is performed. This software allows for rapid exploration of the Fermi data, simulation of the source detection to calculate the selection function of various sources and the errors in the obtained parameters of the sources detected.
104 - Changli Ma , Yao Zhang , Ye Yuan 2013
A pattern matching based tracking algorithm, named MdcPatRec, is used for the reconstruction of charged tracks in the drift chamber of the BESIII detector. This paper addresses the shortage of segment finding in MdcPatRec algorithm. An extended segme nt construction scheme and the corresponding pattern dictionary are presented. Evaluation with Monte-Carlo and experimental data show that the new method can achieve higher efficiency for low transverse momentum tracks.
التعليقات
جاري جلب التعليقات جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا