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Title: Cross-language framework for word recognition and spotting of Indic scripts
Authors: Bhunia A.K.
Pratim Roy, Partha
Mohta A.
Pal U.
Published in: Pattern Recognition
Abstract: Handwritten word recognition and spotting of low-resource scripts are difficult as sufficient training data is not available and it is often expensive for collecting data of such scripts. This paper presents a novel cross language platform for handwritten word recognition and spotting for such low-resource scripts where training is performed with a sufficiently large dataset of an available script (considered as source script) and testing is done on other scripts (considered as target script). Training with one source script and testing with another script to have a reasonable result is not easy in handwriting domain due to the complex nature of handwriting variability among scripts. Also it is difficult in mapping between source and target characters when they appear in cursive word images. The proposed Indic cross language framework exploits a large resource of dataset for training and uses it for recognizing and spotting text of other target scripts where sufficient amount of training data is not available. Since, Indic scripts are mostly written in 3 zones, namely, upper, middle and lower, we employ zone-wise character (or component) mapping for efficient learning purpose. The performance of our cross-language framework depends on the extent of similarity between the source and target scripts. Hence, we devise an entropy based script similarity score using source to target character mapping that will provide a feasibility of cross language transcription. We have tested our approach in three Indic scripts, namely, Bangla, Devanagari and Gurumukhi, and the corresponding results are reported. © 2018 Elsevier Ltd
Citation: Pattern Recognition (2018), 79(): 12-31
Issue Date: 2018
Publisher: Elsevier Ltd
Keywords: Cross language recognition
Handwritten word recognition
Hidden Markov model
Indic script recognition
Script similarity
Word spotting
ISSN: 313203
Author Scopus IDs: 57188719920
Author Affiliations: Bhunia, A.K., Dept. of ECE, Institute of Engineering & Management, Kolkata, India
Roy, P.P., Dept. of CSE, Indian Institute of Technology, Roorkee, India
Mohta, A., Dept. of ECE, Institute of Engineering & Management, Kolkata, India
Pal, U., CVPR Unit, Indian Statistical Institute, Kolkata, India
Corresponding Author: Roy, P.P.; Dept. of CSE, Indian Institute of TechnologyIndia; email:
Appears in Collections:Journal Publications [CS]

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