Evaluation of GIST operator for document image retrieval

Alaei, F; Alaei, A; Pal, U; Blumenstein, M

Evaluation of GIST operator for document image retrieval

Alaei, F Alaei, A Pal, U Blumenstein, M

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Publication Type:: Conference Proceeding
Citation:: Proceedings - 13th IAPR International Workshop on Document Analysis Systems, DAS 2018, 2018, pp. 369 - 374
Issue Date:: 2018-06-22

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Field	Value	Language
dc.contributor.author	Alaei, F	en_US
dc.contributor.author	Alaei, A	en_US
dc.contributor.author	Pal, U	en_US
dc.contributor.author	Blumenstein, M https://orcid.org/0000-0002-9908-3744	en_US
dc.date.issued	2018-06-22	en_US
dc.identifier.citation	Proceedings - 13th IAPR International Workshop on Document Analysis Systems, DAS 2018, 2018, pp. 369 - 374	en_US
dc.identifier.isbn	9781538633465	en_US
dc.identifier.uri	http://hdl.handle.net/10453/133289
dc.description.abstract	© 2018 IEEE. As digitised documents normally contain a large variety of structures, a page segmentation-and layout-free method for document image retrieval is preferable. In this research work, therefore, wavelet transform as a transform-based approach is initially used to provide different under-sampled images from the original image. Then, GIST operator, as a feature extraction technique, is employed to extract a set of global features from the original image as well as the sub-images obtained from the wavelet transform. Moreover, the column-wise variances of the values in each sub-image are computed and they are then concatenated to obtain another set of features. Considering each feature set, locality-sensitive hashing is employed to compute similarity distances between a query and the document images in the database. Finally, a classifier fusion technique using the mean function is taken into account to provide a document image retrieval result. The combination of these features and a clustering score fusion strategy provides higher document image retrieval accuracy. Two different databases of the document image are considered for experimentation. The results obtained from the experimental study are detailed and the results are encouraging.	en_US
dc.relation.ispartof	Proceedings - 13th IAPR International Workshop on Document Analysis Systems, DAS 2018	en_US
dc.relation.isbasedon	10.1109/DAS.2018.43	en_US
dc.title	Evaluation of GIST operator for document image retrieval	en_US
dc.type	Conference Proceeding
utslib.for	0806 Information Systems	en_US
pubs.embargo.period	Not known	en_US
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 - CAI - Centre for Artificial Intelligence
pubs.organisational-group	/University of Technology Sydney/Strength - QSI - Centre for Quantum Software and Information
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

© 2018 IEEE. As digitised documents normally contain a large variety of structures, a page segmentation-and layout-free method for document image retrieval is preferable. In this research work, therefore, wavelet transform as a transform-based approach is initially used to provide different under-sampled images from the original image. Then, GIST operator, as a feature extraction technique, is employed to extract a set of global features from the original image as well as the sub-images obtained from the wavelet transform. Moreover, the column-wise variances of the values in each sub-image are computed and they are then concatenated to obtain another set of features. Considering each feature set, locality-sensitive hashing is employed to compute similarity distances between a query and the document images in the database. Finally, a classifier fusion technique using the mean function is taken into account to provide a document image retrieval result. The combination of these features and a clustering score fusion strategy provides higher document image retrieval accuracy. Two different databases of the document image are considered for experimentation. The results obtained from the experimental study are detailed and the results are encouraging.

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http://hdl.handle.net/10453/133289