Název:	Coarse Classification of Teeth using Shape Descriptors
Autoři:	Gosciewska, Katarzyna Frejlichowski, Dariusz
Citace zdrojového dokumentu:	WSCG 2020: full papers proceedings: 28th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, p. 11-18.
Datum vydání:	2020
Nakladatel:	Václav Skala - UNION Agency
Typ dokumentu:	conferenceObject konferenční příspěvek
URI:	http://wscg.zcu.cz/WSCG2020/2020-CSRN-3001.pdf http://hdl.handle.net/11025/38446
ISBN:	978-80-86943-35-0
ISSN:	2464–4617 (print) 2464–4625 (CD-ROM)
Klíčová slova:	oddělení zubů;hrubá klasifikace;deskriptory tvaru;redukce dat;rentgenové snímky
Klíčová slova v dalším jazyce:	teeth separation;coarse classification;shape descriptors;data reduction;dental radiographs
Abstrakt v dalším jazyce:	This paper presents the problem of coarse classification in an application to teeth shapes. Coarse classification allows to separate a set of objects into several general classes and can precede more detailed identification or narrow the search space. Features of an object are mainly determined by its geometrical aspects, therefore we investigate the use of shape description algorithms, namely the Two-Dimensional Fourier Descriptor, UNL-Fourier Descriptor, Generic Fourier Descriptor, Curvature Scale Space, Zernike Moments and Point Distance Histogram. During the experiments we examine the accuracy of classification into two classes: single-rooted teeth and multi-rooted teeth—each class has five representatives. We also employ an additional step of data reduction. Reduced representations are obtained in three ways: by taking a part of an original representation, by predefining a shape description algorithm parameter or by applying an additional step of data reduction technique, i.e. the Principal Component Analysis or Linear Discriminant Analysis. Euclidean distance is used to match final feature vectors with class representatives in order to indicate the most similar one. The experimental results proved the effectiveness of the proposed approach.
Práva:	© Václav Skala - UNION Agency
Vyskytuje se v kolekcích:	WSCG 2020: Full Papers Proceedings

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