"Content Based Image Retrieval System (CBIR) is used to retrieve images similar to the query image. These systems have a wide range of applications in various fields. Medical subject headings, key words, and bibliographic references can be augmented with the images present within the articles to help clinicians to potentially improve the relevance of articles found in the querying process. In this research, image feature analysis and classification techniques are explored to differentiate images found in biomedical articles which have been categorized based on modality and utility. Examples of features examined in this research include: features based on different histograms of the image, texture features, fractal dimensions etc. Classification algorithms used for categorization were 1) Mean shift clustering 2) Radial basis clustering. Different combinations of features were selected for classification purposes and it was observed that features incorporating soft decision based HSV histogram features give the best results. A library of features was then developed which can be used in RapidMiner. Experimental results for various combinations of features have also been included"--Abstract, page iii.
Stanley, R. Joe
Wilkerson, Ralph W.
M.S. in Computer Science
National Library of Medicine (U.S.)
Missouri University of Science and Technology
xi, 84 pages
© 2010 Vikas Nahar, All rights reserved.
Thesis - Open Access
Content-based image retrieval
Image analysis -- Technique
Optical character recognition devices -- Computer programs
Print OCLC #
Electronic OCLC #
Link to Catalog Record
Nahar, Vikas, "Content based image retrieval for bio-medical images" (2010). Masters Theses. 6856.