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Computer Optics, 2018, Volume 42, Issue 2, Pages 273–282
DOI: https://doi.org/10.18287/2412-6179-2018-42-2-273-282
(Mi co504)
 

This article is cited in 6 scientific papers (total in 6 papers)

IMAGE PROCESSING, PATTERN RECOGNITION

Theoretical foundations of hypertrace-transform: scanning techniques, mathematical apparatus and experimental verification

N. G. Fedotova, A. A. Syemovb, A. V. Moiseeva

a Penza State University, Penza, Russia
b LLC «KomHelf», Penza, Russia
Full-text PDF (442 kB) Citations (6)
References:
Abstract: We consistently describe the theoretical basis of a new geometric method of analysis and recognition of three-dimensional (3D) images. The description of a scanning technique for forming a hypertrace transform and its mathematical model are given. This method, unlike the existing ones, enables 3D images to be analyzed directly from their 3D shape, without first simplifying them or constructing plane projections. We substantiate the selection of a particular scanning tool and the need to construct a reference spherical grid to address the problem of the rotational invariance of the 3D image recognition. A mathematical apparatus of the stochastic realization of the scanning technique based on stochastic geometry and functional analysis is developed. We introduce a new mathematical tool for 3D image analysis – a hypertrex matrix that allows spatial objects of complex shape and structure to be recognized by constructing a single mathematical model of the 3D image. We describe a new type of 3D image features that have an analytic structure – hypertryplet features, whose analytical structure makes possible an automatic generation of a large number of features with predetermined properties. Results of the experimental verification are presented, demonstrating the accurate calculation of features for 3D image recognition and proving the adequacy of the developed mathematical apparatus.
Keywords: recognition of 3D images, geometric hypertrace-transform, grid of parallel planes, stochastic scanning, analytical structure of the feature, hypertrace matrix, and invariant recognition.
Funding agency Grant number
Russian Foundation for Basic Research 15-07-04484
The work was partially funded by the Russian Foundation for Basic Research under grant No. 15-07-04484.
Received: 09.08.2017
Accepted: 16.10.2017
Document Type: Article
Language: Russian
Citation: N. G. Fedotov, A. A. Syemov, A. V. Moiseev, “Theoretical foundations of hypertrace-transform: scanning techniques, mathematical apparatus and experimental verification”, Computer Optics, 42:2 (2018), 273–282
Citation in format AMSBIB
\Bibitem{FedSyeMoi18}
\by N.~G.~Fedotov, A.~A.~Syemov, A.~V.~Moiseev
\paper Theoretical foundations of hypertrace-transform: scanning techniques, mathematical apparatus and experimental verification
\jour Computer Optics
\yr 2018
\vol 42
\issue 2
\pages 273--282
\mathnet{http://mi.mathnet.ru/co504}
\crossref{https://doi.org/10.18287/2412-6179-2018-42-2-273-282}
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  • https://www.mathnet.ru/eng/co504
  • https://www.mathnet.ru/eng/co/v42/i2/p273
  • This publication is cited in the following 6 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Computer Optics
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    Full-text PDF :54
    References:18
     
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