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Full-Text Articles in Physical Sciences and Mathematics
Mine Boundary Detection Using Partially Ordered Markov Models, Xia Hua, Jennifer Davidson, Noel A. Cressie
Mine Boundary Detection Using Partially Ordered Markov Models, Xia Hua, Jennifer Davidson, Noel A. Cressie
Faculty of Informatics - Papers (Archive)
Detection of objects in images in an automated fashion is necessary for many applications, including automated target recognition. In this paper, we present results of an automated boundary detection procedure using a new subclass of Markov random fields (MRFs), called partially ordered Markov models (POMMs). POMMs offer computational advantages over general MRFs. We show how a POMM can model the boundaries in an image. Our algorithm for boundary detection uses a Bayesian approach to build a posterior boundary model that locates edges of objects having a closed loop boundary. We apply our method to images of mines with very good …
Models And Inference For Clustering Of Locations Of Mines And Minelike Objects, Noel A. Cressie, Andrew B. Lawson
Models And Inference For Clustering Of Locations Of Mines And Minelike Objects, Noel A. Cressie, Andrew B. Lawson
Faculty of Informatics - Papers (Archive)
Mines and mine-like objects are distributed throughout an area of interest. Remote sensing of the area form an aircraft yields image data that represent the superposition of electromagnetic emissions from the mines and mine-like objects. In this article we build a hierarchical statistical model for the reconstruction of mien locations given a point pattern of the superposition of mines and mine-like objects. It is shown how inference on the mine locations can be obtained using Markov chain Monte Carlo methods.