Information retrieval research has shown significant improvement and provided techniques that retrieve documents in image or text form. However, retrieval of multi-modal documents has been given very less attention. We aim to build a system for retrieval of documents with embedded information graphics (Info-graphics). Info-graphics are images of bar charts and line graphs appearing with textual components in magazines, newspapers, and journals. In this paper, we present multi-modal document image retrieval framework by learning an optimal fusion of information from text and info-graphics regions. The evaluation of the proposed concept is demonstrated on documents collected from various sources such as magazines and journals.
CITATION STYLE
Garg, R., & Chaudhury, S. (2016). Info-graphics retrieval: A multi-kernel distance based hashing scheme. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10481 LNCS, pp. 288–298). Springer Verlag. https://doi.org/10.1007/978-3-319-68124-5_25
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