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  1. International Journal of Document Analysis and Recognition (IJDAR)
  2. International Journal of Document Analysis and Recognition (IJDAR) : Volume 14
  3. International Journal of Document Analysis and Recognition (IJDAR) : Volume 14, Issue 2, June 2011
  4. Unconstrained handwritten document retrieval
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International Journal of Document Analysis and Recognition (IJDAR) : Volume 20
International Journal of Document Analysis and Recognition (IJDAR) : Volume 19
International Journal of Document Analysis and Recognition (IJDAR) : Volume 18
International Journal of Document Analysis and Recognition (IJDAR) : Volume 17
International Journal of Document Analysis and Recognition (IJDAR) : Volume 16
International Journal of Document Analysis and Recognition (IJDAR) : Volume 15
International Journal of Document Analysis and Recognition (IJDAR) : Volume 14
International Journal of Document Analysis and Recognition (IJDAR) : Volume 14, Issue 4, December 2011
International Journal of Document Analysis and Recognition (IJDAR) : Volume 14, Issue 3, September 2011
International Journal of Document Analysis and Recognition (IJDAR) : Volume 14, Issue 2, June 2011
Special issue on noisy text analytics
Report from the AND 2009 working group on noisy text datasets
Text retrieval from early printed books
A word spotting framework for historical machine-printed documents
Unconstrained handwritten document retrieval
Towards information retrieval on historical document collections: the role of matching procedures and special lexica
Character confusion versus focus word-based correction of spelling and OCR variants in corpora
Robust named entity detection from optical character recognition output
Domain-specific entity extraction from noisy, unstructured data using ontology-guided search
Supervised semantic relation mining from linguistically noisy text documents
Digital weight watching: reconstruction of scanned documents
International Journal of Document Analysis and Recognition (IJDAR) : Volume 14, Issue 1, March 2011
International Journal of Document Analysis and Recognition (IJDAR) : Volume 13
International Journal of Document Analysis and Recognition (IJDAR) : Volume 12
International Journal of Document Analysis and Recognition (IJDAR) : Volume 11
International Journal of Document Analysis and Recognition (IJDAR) : Volume 10
International Journal of Document Analysis and Recognition (IJDAR) : Volume 9
International Journal of Document Analysis and Recognition (IJDAR) : Volume 8
International Journal of Document Analysis and Recognition (IJDAR) : Volume 7
International Journal of Document Analysis and Recognition (IJDAR) : Volume 6
International Journal of Document Analysis and Recognition (IJDAR) : Volume 5
International Journal of Document Analysis and Recognition (IJDAR) : Volume 4
International Journal of Document Analysis and Recognition (IJDAR) : Volume 3
International Journal of Document Analysis and Recognition (IJDAR) : Volume 2
International Journal of Document Analysis and Recognition (IJDAR) : Volume 1

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Unconstrained handwritten document retrieval

Content Provider SpringerLink
Author Cao, Huaigu Govindaraju, Venu Bhardwaj, Anurag
Copyright Year 2010
Abstract With the ever-increasing growth of the World Wide Web, there is an urgent need for an efficient information retrieval system that can search and retrieve handwritten documents when presented with user queries. However, unconstrained handwriting recognition remains a challenging task with inadequate performance thus proving to be a major hurdle in providing robust search experience in handwritten documents. In this paper, we describe our recent research with focus on information retrieval from noisy text derived from imperfect handwriting recognizers. First, we describe a novel term frequency estimation technique incorporating the word segmentation information inside the retrieval framework to improve the overall system performance. Second, we outline a taxonomy of different techniques used for addressing the noisy text retrieval task. The first method uses a novel bootstrapping mechanism to refine the OCR’ed text and uses the cleaned text for retrieval. The second method uses the uncorrected or raw OCR’ed text but modifies the standard vector space model for handling noisy text issues. The third method employs robust image features to index the documents instead of using noisy OCR’ed text. We describe these techniques in detail and also discuss their performance measures using standard IR evaluation metrics.
Starting Page 145
Ending Page 157
Page Count 13
File Format PDF
ISSN 14332833
Journal International Journal of Document Analysis and Recognition (IJDAR)
Volume Number 14
Issue Number 2
e-ISSN 14332825
Language English
Publisher Springer-Verlag
Publisher Date 2010-11-16
Publisher Place Berlin, Heidelberg
Access Restriction Subscribed
Subject Keyword Image Processing and Computer Vision Pattern Recognition
Content Type Text
Resource Type Article
Subject Computer Vision and Pattern Recognition Software Computer Science Applications
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