NDLI: Classifying Biomedical Figures Using Combination of Bag of Keypoints and Bag of Words

Content Provider	IEEE Xplore Digital Library
Author	Koike, A. Takagi, T.
Copyright Year	2009
Abstract	Figures in full science papers contain much information not described in the main text. The use of these figures is an important subject. In this study, we developed a method to classify these biomedical figures into categories using a combination of a bag of keypoints approach and a bag of words approach for the legends. For bag of keypoints, the descriptors of detected interest points are quantized by k-means clustering and are converted into a feature vector element. The figure classification is carried out using a one-against-all multi-class support vector machine. When the Harris-affine and extended scale-invariant feature transform method are used for interest point detection and feature description, respectively, the classification accuracy of bag of keypoints is about 20% better than that of field-level image descriptors which are similar to descriptors used in previous studies. Further, when bag of words for legends is combined with this method, the prediction performance achieved 75.7% classification accuracy. Introducing bag of keypoints not only increases the classification performance but also enables the figures to be treated as text words. This method is expected to be useful for figure similarity search and information retrieval across figures and text.
Starting Page	848
Ending Page	853
File Size	1207728
Page Count	6
File Format	PDF
ISBN	9781424435692
DOI	10.1109/CISIS.2009.11
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-03-16
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computer vision Image edge detection Vector quantization Natural languages Biomedical computing Presence network agents Data mining Support vector machines Histograms Radiology Software systems Competitive intelligence Image classification
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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