Diferencia entre revisiones de «Hybrid Image Segmentation»
De Grupo de Inteligencia Computacional (GIC)
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: In this page we make publicly available a demonstration of a [[media:HIS.zip| Hybrid Image Segmentation]]method based on a hybrid distance which is inspired in the selective behavior of the human vision system. | : In this page we make publicly available a demonstration of a [[media:HIS.zip| Hybrid Image Segmentation]]method based on a hybrid distance which is inspired in the selective behavior of the human vision system. | ||
: The method has 3 parameters (a,b,c) that specify the mixture model controlling the of activation of each component of the hybrid distance. Besides, the method allows the specification of a decision threshold controlling the sensitivity of the method and the resulting amount of image segmentation regions. | : The method has 3 parameters (a,b,c) that specify the mixture model controlling the of activation of each component of the hybrid distance. Besides, the method allows the specification of a decision threshold controlling the sensitivity of the method and the resulting amount of image segmentation regions. | ||
: The details of the method are given in the paper ***** submitted for publication. | : The details of the method are given in the paper ***** submitted for publication. | ||
: The [[media:SphericClass.zip| Sources]]. This class in C# and contains a lot of methods for image segmentation based on the spheric approach. | |||
: For any question, fell free to ask [http://www.ehu.es/ccwintco/index.php/Usuario:Natafresa me]. | |||
: Platform support: This software has been developed in the .Net platform. | : Platform support: This software has been developed in the .Net platform. | ||
Revisión del 16:08 9 feb 2011
- In this page we make publicly available a demonstration of a Hybrid Image Segmentationmethod based on a hybrid distance which is inspired in the selective behavior of the human vision system.
- The method has 3 parameters (a,b,c) that specify the mixture model controlling the of activation of each component of the hybrid distance. Besides, the method allows the specification of a decision threshold controlling the sensitivity of the method and the resulting amount of image segmentation regions.
- The details of the method are given in the paper ***** submitted for publication.
