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Please use this identifier to cite or link to this item:
http://hdl.handle.net/2080/413
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Full metadata record
| DC Field | Value | Language |
|---|
| contributor.author | Panda, Sucheta | - |
| contributor.author | Nanda, P K | - |
| contributor.author | Mohapatra, P J | - |
| date.accessioned | 2007-03-06T12:06:25Z | - |
| date.available | 2007-03-06T12:06:25Z | - |
| date.issued | 2007 | - |
| identifier.citation | Proceedings of the National Conference on Smart Communication Technologies and Industrial Informatics, SCTII, 03-04 Feb 2007, Rourkela. P 34-42 | en |
| identifier.uri | http://hdl.handle.net/2080/413 | - |
| description | Copyright for this article belongs to National Institute of Technology, Rourkela India | en |
| description.abstract | In this paper, the color image segmentation problem is
addressed in supervised framework. In the supervised
framework, we assume to have one original image from the
class of images from which the given image is derived. In
this framework, We have used Markov Random
Field(MRF) to model the image label process and the MRF
model parameters are estimated using the conditional
pseudolikelihood criterion. Ohta( I1, I2, I3 )model is used as
the color model. The segmentation problem is formulated as
the pixel labeling problem. The image model parameter
estimation problem is formulated using pseudo-likelihood
criterion. The image label estimation problem is cast in
Maximum {a Posteriori} (MAP) framework. These MAP
estimates are obtained using the proposed new hybrid
algorithm and compared with Simulated Annealing (SA)
algorithm. It is observed that the proposed hybrid algorithm
converge much faster than that of SA. The segmentation
scheme is further improved by adhering to multiresolution
approach where the segmentation is carried at a coarse level
and reconstructed to a finer level. The proposed scheme
appears to be more viable from a practical standpoint. | en |
| format.extent | 695329 bytes | - |
| format.mimetype | application/pdf | - |
| language.iso | en | - |
| publisher | National Institute of Technology, Rourkela | en |
| subject | Ohta color Space | en |
| subject | MAP Estimate | en |
| subject | Segmentation | en |
| subject | Simuated Annealing | en |
| subject | Hybrid Algorithm | en |
| title | Multiresolution Approach for Color Image Segmentation using MRF Model | en |
| type | Article | en |
| Appears in Collections: | Conference Papers
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Files in This Item:
| File |
Description |
Size | Format |
|---|
| SCTII07.pdf | | 679Kb | Adobe PDF | View/Open |
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