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Bayesian fusion of color and texture segmentations
| Content Provider | NASA Technical Reports Server (NTRS) |
|---|---|
| Author | Manduchi, Roberto |
| Copyright Year | 2000 |
| Description | In many applications one would like to use information from both color and texture features in order to segment an image. We propose a novel technique to combine "soft" segmentations computed for two or more features independently. Our algorithm merges models according to a mean entropy criterion, and allows to choose the appropriate number of classes for the final grouping. This technique also allows to improve the quality of supervised classification based on one feature (e.g. color) by merging information from unsupervised segmentation based on another feature (e.g., texture.) |
| File Size | 490990 |
| File Format | |
| Language | English |
| Publisher Date | 2000-01-01 |
| Access Restriction | Open |
| Subject Keyword | Optics Cluster Analysis Algorithms Image Processing Color Imaging Techniques Segments Entropy Criteria Pattern Recognition Image Classification Textures Bayes Theorem Ntrs Nasa Technical Reports Server (ntrs) Nasa Technical Reports Server Aerodynamics Aircraft Aerospace Engineering Aerospace Aeronautic Space Science |
| Content Type | Text |
| Resource Type | Technical Report |
