Text-line-up: Don’t Worry About the Caret

Adak, C; Chaudhuri, BB; Lin, CT; Blumenstein, M

Text-line-up: Don’t Worry About the Caret

Adak, C

Chaudhuri, BB Lin, CT Blumenstein, M

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Publisher:: Springer
Publication Type:: Conference Proceeding
Citation:: Document Analysis and Recognition – ICDAR 2021, 2021, 12823 LNCS, pp. 207-222
Issue Date:: 2021-01-01

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Field	Value	Language
dc.contributor.author	Adak, C https://orcid.org/0000-0002-9085-2770
dc.contributor.author	Chaudhuri, BB
dc.contributor.author	Lin, CT
dc.contributor.author	Blumenstein, M https://orcid.org/0000-0002-9908-3744
dc.contributor.editor	Llados, J
dc.contributor.editor	Lopresti, D
dc.contributor.editor	Uchida, S
dc.date	2021-09-05
dc.date.accessioned	2022-06-11T06:21:49Z
dc.date.available	2022-06-11T06:21:49Z
dc.date.issued	2021-01-01
dc.identifier.citation	Document Analysis and Recognition – ICDAR 2021, 2021, 12823 LNCS, pp. 207-222
dc.identifier.isbn	9783030863333
dc.identifier.issn	0302-9743
dc.identifier.issn	1611-3349
dc.identifier.uri	http://hdl.handle.net/10453/158103
dc.description.abstract	In a freestyle handwritten text-line, sometimes words are inserted using a caret symbol (∧ ) for corrections/annotations. Such insertions create fluctuations in the reading sequence of words. In this paper, we aim to line-up the words of a text-line, so that it can assist the OCR engine. Previous text-line segmentation techniques in the literature have scarcely addressed this issue. Here, the task undertaken is formulated as a path planning problem, and a novel multi-agent hierarchical reinforcement learning-based architecture solution is proposed. As a matter of fact, no linguistic knowledge is used here. Experimentation of the proposed solution architecture has been conducted on English and Bengali offline handwriting, which yielded some interesting results.
dc.language	en
dc.publisher	Springer
dc.relation.ispartof	Document Analysis and Recognition – ICDAR 2021
dc.relation.ispartof	International Conference on Document Analysis and Recognition
dc.relation.ispartofseries	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.relation.isbasedon	10.1007/978-3-030-86334-0_14
dc.rights	info:eu-repo/semantics/restrictedAccess
dc.rights	This is a post-peer-review, pre-copyedit version of an article published in [Document Analysis and Recognition ICDAR 2021, 2021, 12823 LNCS, pp. 207-222]. Publication date Published: 01 Jan 2021 ] The final authenticated version is available online at: [ https://link.springer.com/chapter/10.1007/978-3-030-86334-0_14]”
dc.subject.classification	Artificial Intelligence & Image Processing
dc.title	Text-line-up: Don’t Worry About the Caret
dc.type	Conference Proceeding
utslib.citation.volume	12823 LNCS
utslib.location.activity	Lausanne, Switzerland
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - AAII - Australian Artificial Intelligence Institute
pubs.organisational-group	/University of Technology Sydney/Strength - QSI - Centre for Quantum Software and Information
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	in_progress	*
pubs.consider-herdc	false
dc.date.updated	2022-06-11T06:21:47Z
pubs.finish-date	2021-09-10
pubs.place-of-publication	Switzerland
pubs.publication-status	Published
pubs.start-date	2021-09-05
pubs.volume	12823 LNCS
dc.location	Switzerland

Abstract:

In a freestyle handwritten text-line, sometimes words are inserted using a caret symbol (∧ ) for corrections/annotations. Such insertions create fluctuations in the reading sequence of words. In this paper, we aim to line-up the words of a text-line, so that it can assist the OCR engine. Previous text-line segmentation techniques in the literature have scarcely addressed this issue. Here, the task undertaken is formulated as a path planning problem, and a novel multi-agent hierarchical reinforcement learning-based architecture solution is proposed. As a matter of fact, no linguistic knowledge is used here. Experimentation of the proposed solution architecture has been conducted on English and Bengali offline handwriting, which yielded some interesting results.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/158103