Pattern Recognition with Rejection Combining Standard Classification Methods with Geometrical Rejecting

Władysław Homenda , Agnieszka Jastrzębska , Piotr Waszkiewicz , Anna Zawadzka

Abstract

The motivation of our study is to provide algorithmic approaches to distinguish proper patterns, from garbage and erroneous patterns in a pattern recognition problem. The design assumption is to provide methods based on proper patterns only. In this way the approach that we propose is truly versatile and it can be adapted to any pattern recognition problem in an uncertain environment, where garbage patterns may appear. The proposed attempt to recognition with rejection combines known classifiers with geometric methods used for separating native patterns from foreign ones. Empirical verification has been conducted on datasets of handwritten digits classification (native patterns) and handwritten letters of Latin alphabet (foreign patterns).
Author Władysław Homenda (FMIS / DSMKP) - [Faculty of Economics and Informatics in Vilnius, University of Bialystok, Kalvariju G. 135, LT-08221 Vilnius, Lithuania (UwB)]
Władysław Homenda,,
- Department of Structural Methods for Knowledge Processing
- Uniwersytet w Białymstoku, Wydział Ekonomiczno - Informatyczny w Wilnie
, Agnieszka Jastrzębska (FMIS / DSMKP)
Agnieszka Jastrzębska,,
- Department of Structural Methods for Knowledge Processing
, Piotr Waszkiewicz - [Warsaw University of Technology (PW), MNiSW [80]]
Piotr Waszkiewicz,,
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- Politechnika Warszawska
, Anna Zawadzka - Maria Sklodowska-Curie Memorial Cancer Center [Politechnika Warszawska]
Anna Zawadzka,,
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Pages589-602
Publication size in sheets0.65
Book Saeed Khalid, Homenda Władysław (eds.): Computer Information Systems and Industrial Management, Lecture Notes In Computer Science, vol. 9842, 2016, SPRINGER INT PUBLISHING AG, ISBN 978-3-319-45377-4, DOI:10.1007/978-3-319-45378-1_61
Keywords in EnglishPattern recognition; Classification; Rejecting option; Geometrical methods
DOIDOI:10.1007/978-3-319-45378-1_52
Languageen angielski
Score (nominal)15
Score sourceconferenceIndex
ScoreMinisterial score = 15.0, 06-12-2019, BookChapterSeriesAndMatConfByConferenceseries
Ministerial score (2013-2016) = 15.0, 06-12-2019, BookChapterSeriesAndMatConfByConferenceseries
Publication indicators WoS Citations = 1; Scopus Citations = 1
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