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Proceedings Paper

Detection and characterization of carboniferous foraminifera for content-based retrieval from an image database
Author(s): Richard T. Shann; Darryl N. Davis; John P. Oakley; Fiona White
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Paper Abstract

Carboniferous Foraminifers are a specific type of microfossil which are manifest in plane sections of rock and are used by geologists for dating rock samples. The images contain a high degree of visual noise and currently must be interpreted by human experts. We are studying the classification problem in the context of intelligent image databases. Here we present a technique for automatic identification of microfossil structures and for classification of the structures according to which type of 3-D section they represent. This is achieved by using: (1) A specialized filter to detect local curves in the gray level image data; and (2) Hough transform processing of the resulting feature point vectors. An interesting aspect of our approach is that the processing of the features is not embedded in a program but is instead specified using a visual query language. This allows us to experiment quickly with different types of grouping criteria. The detection performance of our system is comparable with that of a trained geologist. We store the information obtained in a database together with the raw image data. The system can then present the user with only those images which contain structures of interest.

Paper Details

Date Published: 14 April 1993
PDF: 10 pages
Proc. SPIE 1908, Storage and Retrieval for Image and Video Databases, (14 April 1993); doi: 10.1117/12.143649
Show Author Affiliations
Richard T. Shann, Manchester Univ. (United Kingdom)
Darryl N. Davis, Manchester Univ. (United Kingdom)
John P. Oakley, Manchester Univ. (United Kingdom)
Fiona White, Manchester Univ. (United Kingdom)

Published in SPIE Proceedings Vol. 1908:
Storage and Retrieval for Image and Video Databases
Carlton Wayne Niblack, Editor(s)

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