Please use this identifier to cite or link to this item: http://gukir.inflibnet.ac.in:8080/jspui/handle/123456789/3764
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dc.contributor.authorRajput G.G
dc.contributor.authorUmmapure S.B.
dc.date.accessioned2020-06-12T15:01:15Z-
dc.date.available2020-06-12T15:01:15Z-
dc.date.issued2018
dc.identifier.citationIEEE International Conference on Power, Control, Signals and Instrumentation Engineering, ICPCSI 2017 , Vol. , , p. 520 - 526en_US
dc.identifier.uri10.1109/ICPCSI.2017.8392348
dc.identifier.urihttp://gukir.inflibnet.ac.in:8080/jspui/handle/123456789/3764-
dc.description.abstractAutomatic identification of scripts from document images helps selecting appropriate OCR for character recognition and content retrieval. In this paper, Scale invariant Feature Transformation (SIFT) based script identification has been proposed. Features are extracted using SIFT approach at word level (two, three or more character words) and KNN classifier has been used to recognize the script. Experiments are performed by extracting the words from document images consisting of English, Kannada, and Devanagari scripts. Overall accuracy reported for the proposed system is 97.65% and 96.71% for bi-script and tri-scripts, respectively. © 2017 IEEE.en_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.subjectbi-script
dc.subjectDocument image
dc.subjectKNN
dc.subjectScale invariant
dc.subjectScript recognition
dc.subjectSIFT
dc.titleScript identification from handwritten documents using SIFT methoden_US
dc.typeConference Paper
Appears in Collections:2. Conference Papers

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