Detection of compound structures using multiple hierarchical segmentations
dc.citation.epage | 2065 | en_US |
dc.citation.spage | 2062 | en_US |
dc.contributor.author | Akçay, Hüseyin Gökhan | en_US |
dc.contributor.author | Aksoy, Selim | en_US |
dc.coverage.spatial | Trabzon, Turkey | en_US |
dc.coverage.spatial | Trabzon, Turkey | en_US |
dc.date.accessioned | 2016-02-08T11:45:03Z | |
dc.date.available | 2016-02-08T11:45:03Z | |
dc.date.issued | 2014 | en_US |
dc.department | Department of Computer Engineering | en_US |
dc.description | Date of Conference: 23-25 April 2014 | en_US |
dc.description.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. | en_US |
dc.description.provenance | Made available in DSpace on 2016-02-08T11:45:03Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2014 | en |
dc.identifier.doi | 10.1109/SIU.2014.6830666 | en_US |
dc.identifier.uri | http://hdl.handle.net/11693/27119 | |
dc.language.iso | Turkish | en_US |
dc.publisher | IEEE | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1109/SIU.2014.6830666 | en_US |
dc.source.title | 2014 22nd Signal Processing and Communications Applications Conference (SIU) | en_US |
dc.subject | Markov processes | en_US |
dc.subject | Signal processing | en_US |
dc.subject | Compound structures | en_US |
dc.subject | Context modeling | en_US |
dc.subject | Hierarchical segmentation | en_US |
dc.subject | High resolution image | en_US |
dc.subject | Markov Random Fields | en_US |
dc.subject | Maximum entropy distribution | en_US |
dc.subject | Probabilistic modeling | en_US |
dc.subject | Spatial arrangements | en_US |
dc.subject | Query processing | en_US |
dc.title | Detection of compound structures using multiple hierarchical segmentations | en_US |
dc.title.alternative | Bileşik yapilarin Coklu siradüzensel bölütlemeler kullanilarak sezimi | en_US |
dc.type | Conference Paper | en_US |
Files
Original bundle
1 - 1 of 1
Loading...
- Name:
- Detection of compound structures using multiple hierarchical segmentations [Bileşik yapilarin Coklu siradüzensel bölütlemeler kullanilarak sezimi].pdf
- Size:
- 1.96 MB
- Format:
- Adobe Portable Document Format
- Description:
- Full printable version