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 Bibliografske baze podataka

Pregled bibliografske jedinice broj: 607022

Časopis

Autori: Karić, Miran; Martinović, Goran
Naslov: Improving Offline Handwritten Digit Recognition Using Concavity-based Features
Izvornik: International Journal of Computers Communications & Control (1841-9836) 8 (2013), 2; 206-219
Vrsta rada: članak
Ključne riječi: complementary features; concavity features; digit recognition; feature extraction; handwritten character recognition; off-line recognition
Sažetak:
This paper examines benefits of using concavity-based structural features in recognition of handwritten digits. An overview of existing concavity features is presented and a new method is introduced. These features are used as complementary features to gradient and chaincode features, both among the best performing features in handwritten digit recognition. Two support vector classifiers (SVCs) are chosen for classification task as the top performers in previous works ; SVC with radial basis function (RBF) kernel and the SVC with polynomial kernel. For reference, we also used the k-nearest neighbor (k-NN) classifier. Results are obtained on MNIST, USPS and DIGITS datasets. We also tested dataset independency of various feature vectors by combining different datasets. The introduced feature extraction method gives the best results in majority of tests.
Projekt / tema: 165-0362980-2002, 165-0361621-2000
Izvorni jezik: ENG
Rad je citiran u
bazama podataka:
Web of Science: Science Citation
Web of Science: Science Citation Index Expanded
Scopus
Kategorija: Znanstveni
Znanstvena područja:
Računarstvo
URL Internet adrese: http://univagora.ro/jour/index.php/ijccc/article/view/303
URL cjelovitog teksta: http://univagora.ro/jour/index.php/ijccc/article/view/303
Google Scholar: Improving Offline Handwritten Digit Recognition Using Concavity-based Features
Upisao u CROSBI: gmartin@etfos.hr (gmartin@etfos.hr), 10. Pro. 2012. u 10:21 sati



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