Abstract
Office automation is an active area of research. It involves archival and retrieval of official documents. For developing a system for this purpose, it is necessary to have an extensive benchmark dataset consisting various types of official documents. However, it is hard to make available real world official documents as they are mostly confidential. In the absence of such benchmark datasets, it is difficult to evaluate newly developed algorithms. Hence, efforts have been made to build dataset consisting of different categories of documents that resemble real world official documents. In this work, we present a dataset called as scanned pseudo-official data-set (SPODS) which is created by us and made available online. Official documents are usually distinguished by presence of logo, stamp, signature, date, etc. The paper also presents a new approach for the detection of logo, stamp, and signature using spectral filtering and part based features. A comparative study on performances of the proposed method and existing algorithms on the SPODS dataset demonstrates the effectiveness of the proposed technique.
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The dataset is available at http://www.facweb.iitkgp.ernet.in/~jay/spods/.
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Acknowledgments
This work is partially sponsored by the Ministry of Communications & Information Technology, Govt. of India; Ref.: MCIT 11(19)/2010-HCC (TDIL) dt. 28-12-2010.
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Nandedkar, A.V., Mukherjee, J., Sural, S. (2017). SPODS: A Dataset of Color-Official Documents and Detection of Logo, Stamp, and Signature. In: Mukherjee, S., et al. Computer Vision, Graphics, and Image Processing. ICVGIP 2016. Lecture Notes in Computer Science(), vol 10481. Springer, Cham. https://doi.org/10.1007/978-3-319-68124-5_19
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