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Word level multi-script identification

Publication Type : Journal Article

Publisher : Pattern Recognition Letters

Source : Pattern Recognition Letters, Volume 29, Number 9, p.1218-1229 (2008)

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Keywords : DCT, Gabor filter, Script identification

Campus : Bengaluru

School : Department of Computer Science and Engineering, School of Engineering

Department : Computer Science

Year : 2008

Abstract : We report an algorithm to identify the script of each word in a document image. We start with a bi-script scenario which is later extended to tri-script and then to eleven-script scenarios. A database of 20,000 words of different font styles and sizes has been collected and used for each script. Effectiveness of Gabor and discrete cosine transform (DCT) features has been independently evaluated using nearest neighbor, linear discriminant and support vector machines (SVM) classifiers. The combination of Gabor features with nearest neighbor or SVM classifier shows promising results; i.e., over 98% for bi-script and tri-script cases and above 89% for the eleven-script scenario.

Cite this Research Publication : Peeta Basa Pati and Ramakrishnan, A. G., “Word level multi-script identification”, Pattern Recognition Letters, vol. 29, pp. 1218-1229, 2008.

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