Title

Document image retrieval based on texture features: a recognition-free approach

Document Type

Conference publication

Publication details

Alaei, F, Alaei, A, Pal, U & Blumenstein, M 2016, 'Document image retrieval based on texture features: a recognition-free approach', in Proceedings of the International Conference on Digital Image Computing: Techniques and Applications (DICTA), Gold Coast, Queensland, 30 November - 2 December, IEEE, USA, ISBN: 9781509028962

Published version available from

http://dx.doi.org/10.1109/DICTA.2016.7797033

Peer Reviewed

Peer-Reviewed

Abstract

The tendency of current technology is towards a paperless world. Due to the rapid increase of digitized documents, providing a fast and easy method for retrieval is in high demand. The aim of this paper is to examine the effectiveness of texture features for document image retrieval. Thus, segmentation-free document image retrieval using a binary texture method is proposed. In the proposed approach, local features are extracted, local grey-level structures are summarised, and their distribution is characterised using global features. The assumption is that texture properties in the text regions and non-text regions of the document images are different. This assumption is used to rank the available document images and retrieve only those, which have greatest visual similarity to a given query. The under-sampled image and sub-images of the original image are further considered to improve the retrieval results, which are up to 76.0% in the first ranking and 96.2% in the Top-10 ranking. The Media Team Oulu Document Database, which is a heterogeneous database that offers a great variety of page layouts and contents, is used for experimentation.

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