Figure Based Biomedical Document Retrieval System using Structural Image Features

Figure Based Biomedical Document Retrieval System using Structural Image Features

Harikrishna G. N. Rai, K Sai Deepak, P. Radha Krishna
Copyright: © 2012 |Volume: 3 |Issue: 1 |Pages: 20
ISSN: 1947-9115|EISSN: 1947-9123|EISBN13: 9781466613218|DOI: 10.4018/jkdb.2012010103
Cite Article Cite Article

MLA

Rai, Harikrishna G. N., et al. "Figure Based Biomedical Document Retrieval System using Structural Image Features." IJKDB vol.3, no.1 2012: pp.39-58. http://doi.org/10.4018/jkdb.2012010103

APA

Rai, H. G., Deepak, K. S., & Krishna, P. R. (2012). Figure Based Biomedical Document Retrieval System using Structural Image Features. International Journal of Knowledge Discovery in Bioinformatics (IJKDB), 3(1), 39-58. http://doi.org/10.4018/jkdb.2012010103

Chicago

Rai, Harikrishna G. N., K Sai Deepak, and P. Radha Krishna. "Figure Based Biomedical Document Retrieval System using Structural Image Features," International Journal of Knowledge Discovery in Bioinformatics (IJKDB) 3, no.1: 39-58. http://doi.org/10.4018/jkdb.2012010103

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

Multi-modal and Unstructured nature of documents make their retrieval from healthcare document repositories a challenging task. Text based retrieval is the conventional approach used for solving this problem. In this paper, the authors explore an alternate avenue of using embedded figures for the retrieval task. Usually, context of a document is directly reflected in the associated figures, therefore embedded text within these figures along with image features have been used for similarity based retrieval of figures. The present work demonstrates that image features describing the structural properties of figures are sufficient for the figure retrieval task. First, the authors analyze the problem of figure retrieval from biomedical literature and identify significant classes of figures. Second, they use edge information as a means to discriminate between structural properties of each figure category. Finally, the authors present a methodology using a novel feature descriptor namely Fourier Edge Orientation Autocorrelogram (FEOAC) to describe structural properties of figures and build an effective Biomedical document retrieval system. The experimental results demonstrate the better retrieval performance and overall improvement of FEOAC for figure retrieval task, especially when most of the edge information is retained. Apart from invariance to scale, rotation and non-uniform illumination, the proposed feature descriptor is shown to be relatively robust to noisy edges.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.