UPCommons està en procés de migració del dia 10 fins al 14 Juliol. L’autentificació està deshabilitada per evitar canvis durant aquesta migració.
Innovative applications of associative morphological memories for image processing and pattern recognition

View/Open
Cita com:
hdl:2099/1774
Document typeArticle
Defense date2003
PublisherUniversitat Politècnica de Catalunya. Secció de Matemàtiques i Informàtica
Rights accessOpen Access
This work is protected by the corresponding intellectual and industrial property rights.
Except where otherwise noted, its contents are licensed under a Creative Commons license
:
Attribution-NonCommercial-NoDerivs 3.0 Spain
Abstract
Morphological Associative Memories have been proposed for some image denoising applications. They can be applied to other less restricted domains, like image retrieval and hyper spectral image unsupervised segmentation. In this paper we present these applications. In both cases the key idea is that Autoassociative Morphological Memories selective sensitivity to erosive and dilative noise can be applied to detect the morphological independence between patterns. Linear unmixing based on the sets of morphological independent patterns define a feature extraction process that is the basis for the image processing applications. We discuss some experimental results on the fish shape data base and on a synthetic hyperspectral image, including the comparison with other linear feature extraction algorithms (ICA and CCA).
ISSN1134-5632
Collections
Files | Description | Size | Format | View |
---|---|---|---|---|
article.pdf | 454,8Kb | View/Open |