ALGORITHM OF FORMING AND SELECTING OF INFORMATIVE FEATURES IN CORRELATION EXTREME NAVIGATION SYSTEM DATABASE
DOI:
https://doi.org/10.18372/1990-5548.47.10292Keywords:
Feature selection, maximum entropy method, correlation weighting, Speed-Up Robust Feature, template informativityAbstract
Hierarchical approach to data fusion in complex navigation system is proposed. Low level ofdata processing in correlation extreme navigation system includes forming and selecting the most informativerelevant features. Advanced algorithm is therefore developed based on weighting correlationsampling of template features. Practical efficiency of algorithm is researched based on Speed-Up RobustFeature method of feature points detection and description. Minimization of feature points number intemplate without decreasing the quality of matching is observed along with reduction of computationalcostsReferences
M.P. Mukhina. “Prospects of development correlation-extreme modern navigation systems”. AVIA-2013: Materials of the XI International scientific technical conference. Kyiv: NAU, 2013. pp. 22.1–22.4.
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Herbert Bay, Tinne Tuytelaars, Luc Van Gool. SURF: Speeded Up Robust Features. – Katholieke Universiteit Leuven. 2007. 13 p
Koller D., Sahami M. Toward optimal feature selection. – Machine Learning: Proceedings of the 13-th International Conference on Machine Learning. 1996. Code of SURF listing in MATLAB. Available from Internet:
http://www.mathworks.com/matlabcentral/fileexchan ge/28300-opensurf-including-image-warp
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