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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/15984
Title: Word spotting based on pyramidal histogram of characters code for handwritten text documents
Authors: Ali T.
Pratim Roy, Partha
Chaudhuri B.B.
Raman B.
Kankanhalli M.S.
Published in: Proceedings of Advances in Intelligent Systems and Computing
Abstract: In this work, we propose a three-phase convolutional neural network-based approach for word spotting in handwritten text documents. The system uses a reconstructive convolutional neural network model for segmentation of text document into words. The segmented words are converted into pyramidal histogram of characters code for text representation using modified PHOCNet model. Finally, edit distance is used as a similarity measure between query word and word from text repository. The system is capable of answering the query by example as well as query by a string. The proposed model is also very robust and flexible for the availability of handwritten document repository as training data. The proposed model is validated on IAM dataset of handwritten documents which have 1539 different handwritten text documents from 657 writers. © Springer Nature Singapore Pte Ltd. 2018.
Citation: Proceedings of Advances in Intelligent Systems and Computing, (2018), 379- 389
URI: https://doi.org/10.1007/978-981-10-7898-9_31
http://repository.iitr.ac.in/handle/123456789/15984
Issue Date: 2018
Publisher: Springer Verlag
Keywords: Convolutional neural network
Edit distance
Histogram of characters
Word spotting
ISBN: 9.78981E+12
ISSN: 21945357
Author Scopus IDs: 55314607400
56880478500
Author Affiliations: Ali, T., Department of Computer Science and Engineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India
Roy, P.P., Department of Computer Science and Engineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India
Corresponding Author: Ali, T.; Department of Computer Science and Engineering, Indian Institute of Technology RoorkeeIndia; email: tofik.ali7@gmail.com
Appears in Collections:Conference Publications [CS]

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