Detection of compound structures using multiple hierarchical segmentations

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Detection of compound structures using multiple hierarchical segmentations [Bileşik yapilarin Coklu siradüzensel bölütlemeler kullanilarak sezimi].pdf (1.96 MB)

Date

2014

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Source Title

2014 22nd Signal Processing and Communications Applications Conference (SIU)

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Publisher

IEEE

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2062 - 2065

Language

Turkish

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Conference Paper

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Abstract

In this paper, we present a method for automatic compound structure detection in high-resolution images. Given a query compound structure, our aim is to detect coherent regions with similar spatial arrangement and characteristics in multiple hierarchical segmentations. A Markov random field is constructed by representing query regions as variables and connecting the vertices that are spatially close by edges. Then, a maximum entropy distribution is assumed over the query region process and selection of similar region processes among a set of region hierarchies is achieved by maximizing the query model. Experiments using WorldView-2 images show the efficiency of probabilistic modeling of compound structures. © 2014 IEEE.

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Keywords

Markov processes , Signal processing , Compound structures , Context modeling , Hierarchical segmentation , High resolution image , Markov Random Fields , Maximum entropy distribution , Probabilistic modeling , Spatial arrangements , Query processing

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http://hdl.handle.net/11693/27119

Published Version (Please cite this version)

http://dx.doi.org/10.1109/SIU.2014.6830666

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Scholarly Publications - Computer Engineering