Skip navigation
Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/5650
Title: Logo and seal based administrative document image retrieval: A survey
Authors: Alaei A.
Pratim Roy, Partha
Pal U.
Published in: Computer Science Review
Abstract: With the advance of technology, business offices and organizations together with their clients create a massive amount of administrative documents every day. Administrative documents commonly contain some salient entities such as logos, stamps or seals as the means of their authentication and proprietorship. These salient entities provide quite discriminative information, which can effectively be used for different tasks of document image retrieval, classification and recognition in document-based applications. Thus, proper detection/recognition of these entities in document images increases the performance of such applications in terms of document retrieval, classification, and recognition. To present the state-of-the-art research on the retrieval of administrative document images, this paper deals with a survey of administrative document image retrieval in relation to seals and logos. All the available datasets, feature extraction and classification techniques for logo and seal detection/recognition are discussed systematically. The shortcomings of the present technologies on logo and seal based document processing are also highlighted. Avenues of the future works are further given for the benefit of readers. To the best of authors’ knowledge, there is no survey on administrative document image retrieval and hence the authors hope that this work will be helpful to the researchers of the document analysis community. © 2016 Elsevier Inc.
Citation: Computer Science Review (2016), 22(): 47-63
URI: https://doi.org/10.1016/j.cosrev.2016.09.002
http://repository.iitr.ac.in/handle/123456789/5650
Issue Date: 2016
Publisher: Elsevier Ireland Ltd
Keywords: Administrative document image
Detection
Logo
Recognition
Retrieval
Seal
ISSN: 15740137
Author Scopus IDs: 26427996000
56880478500
57200742116
Author Affiliations: Alaei, A., Laboratoire d'Informatique (LI EA6300), Université François-Rabelais de Tours, France
Roy, P.P., Department of Computer Science & Engineering, Indian Institute of Technology Roorkee, India
Pal, U., Computer Vision and Pattern Recognition Unit, Indian Statistical Institute, Kolkata, 108, India
Corresponding Author: Roy, P.P.; Department of Computer Science & Engineering, Indian Institute of Technology RoorkeeIndia; email: proy.fcs@iitr.ac.in
Appears in Collections:Journal Publications [CS]

Files in This Item:
There are no files associated with this item.
Show full item record


Items in Repository are protected by copyright, with all rights reserved, unless otherwise indicated.