Detection and characterization of carboniferous foraminifera for content-based retrieval from an image database
Richard T. Shann, Darryl N. Davis, John P. Oakley, Fiona White · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1993
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.