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• W1870869614 abstract "India is a multi-lingual country where Roman script is often used alongside different Indic scripts in a text document. To develop a script specific handwritten Optical Character Recognition (OCR) system, it is therefore necessary to identify the scripts of handwritten text correctly. In this paper, we present a system, which automatically separates the scripts of handwritten words from a document, written in Bangla or Devanagri mixed with Roman scripts. In this script separation technique, we first, extract the text lines and words from document pages using a script independent Neighboring Component Analysis technique (1). Then we have designed a Multi Layer Perceptron (MLP) based classifier for script separation, trained with 8 different word- level holistic features. Two equal sized datasets, one with Bangla and Roman scripts and the other with Devanagri and Roman scripts, are prepared for the system evaluation. On respective independent text samples, word-level script identification accuracies of 99.29% and 98.43% are achieved." @default.
• W1870869614 created "2016-06-24" @default.
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• W1870869614 date "2010-02-21" @default.
• W1870869614 modified "2023-09-27" @default.
• W1870869614 title "Word level Script Identification from Bangla and Devanagri Handwritten Texts mixed with Roman Script" @default.
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