Biometric identification with limited data set
Sometimes, in real life, there is only limited information which can be obtained. This situation can be a challenge for the recognition system. The most suitable method to produce best performance needs to be developed. In this paper, small database with limited training data, 50 total images that w...
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my.iium.irep.723732019-05-28T07:19:27Z http://irep.iium.edu.my/72373/ Biometric identification with limited data set Lionnie, Regina Attamimi, Said Sediono, Wahju Alaydrus, Mudrik TK7885 Computer engineering Sometimes, in real life, there is only limited information which can be obtained. This situation can be a challenge for the recognition system. The most suitable method to produce best performance needs to be developed. In this paper, small database with limited training data, 50 total images that were obtained from 25 people, with only 2 images for every respondent were tested in the recognition system. The SIFT algorithm was utilized and also compared with other methods such as Haar wavelet transform, principal component analysis and hierarchical Gaussian scale-space. The best recognition precision was produced by SIFT algorithm which was 38%, while other methods only gave out 30-32% precision of recognition. IEEE 2019-04-18 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/72373/7/72373%20Biometric%20Identification%20with%20Limited%20Data%20Set.pdf application/pdf en http://irep.iium.edu.my/72373/10/72373%20Biometric%20Identification%20SCOPUS.pdf Lionnie, Regina and Attamimi, Said and Sediono, Wahju and Alaydrus, Mudrik (2019) Biometric identification with limited data set. In: 2018 Electrical Power, Electronics, Communications, Controls and Informatics Seminar (EECCIS), 9th-11th October 2018, Batu, East Java, Indonesia. https://ieeexplore.ieee.org/document/8692859 10.1109/EECCIS.2018.8692859 |
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TK7885 Computer engineering Lionnie, Regina Attamimi, Said Sediono, Wahju Alaydrus, Mudrik Biometric identification with limited data set |
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Sometimes, in real life, there is only limited information which can be obtained. This situation can be a challenge for the recognition system. The most suitable method to produce best performance needs to be developed. In this paper, small database with limited training data, 50 total images that were obtained from 25 people, with only 2 images for every respondent were tested in the recognition system. The SIFT algorithm was utilized and also compared with other methods such as Haar wavelet transform, principal component analysis and hierarchical Gaussian scale-space. The best recognition precision was produced by SIFT algorithm which was 38%, while other methods only gave out 30-32% precision of recognition. |
format |
Conference or Workshop Item |
author |
Lionnie, Regina Attamimi, Said Sediono, Wahju Alaydrus, Mudrik |
author_facet |
Lionnie, Regina Attamimi, Said Sediono, Wahju Alaydrus, Mudrik |
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Lionnie, Regina |
title |
Biometric identification with limited data set |
title_short |
Biometric identification with limited data set |
title_full |
Biometric identification with limited data set |
title_fullStr |
Biometric identification with limited data set |
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Biometric identification with limited data set |
title_sort |
biometric identification with limited data set |
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IEEE |
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2019 |
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http://irep.iium.edu.my/72373/7/72373%20Biometric%20Identification%20with%20Limited%20Data%20Set.pdf http://irep.iium.edu.my/72373/10/72373%20Biometric%20Identification%20SCOPUS.pdf http://irep.iium.edu.my/72373/ https://ieeexplore.ieee.org/document/8692859 |
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