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dc.contributor.authorAlaei A.-
dc.contributor.authorPratim Roy, Partha-
dc.contributor.authorPal U.-
dc.identifier.citationComputer Science Review (2016), 22(): 47-63-
dc.description.abstractWith 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.-
dc.publisherElsevier Ireland Ltd-
dc.relation.ispartofComputer Science Review-
dc.subjectAdministrative document image-
dc.titleLogo and seal based administrative document image retrieval: A survey-
dc.affiliationAlaei, A., Laboratoire d'Informatique (LI EA6300), Université François-Rabelais de Tours, France-
dc.affiliationRoy, P.P., Department of Computer Science & Engineering, Indian Institute of Technology Roorkee, India-
dc.affiliationPal, U., Computer Vision and Pattern Recognition Unit, Indian Statistical Institute, Kolkata, 108, India-
dc.description.correspondingauthorRoy, P.P.; Department of Computer Science & Engineering, Indian Institute of Technology RoorkeeIndia; email:
Appears in Collections:Journal Publications [CS]

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