Diferencia entre revisiones de «Robotic Vision: Technologies for Machine Learning and Vision Applications»
De Grupo de Inteligencia Computacional (GIC)
Sin resumen de edición |
Sin resumen de edición |
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:In this page we make publicly available a demonstration of a watershed Image Segmentation method based on a hybrid | :In this page we make publicly available a demonstration of a watershed Image Segmentation method based on a hybrid gradient. | ||
:The method has 2 parameters (a,b) that specify the mixture model controlling the of activation of each component of | :The method has 2 parameters (a,b) that specify the mixture model controlling the of activation of each component of the hybrid gradient. Besides, the method allows the specification of a decision threshold controlling the sensitivity of the method the region mergin. | ||
: For a fast test of the parameters (a,b, threshold). We shared this light application for Windows platforms [media: Hybrid_Watershed_Image Segmentation.zip] | : For a fast test of the parameters (a,b, threshold). We shared this light application for Windows platforms [media: Hybrid_Watershed_Image Segmentation.zip| application] | ||
: The [[media:SphericClass.zip| Sources]]. This class in C# and contains some methods for image segmentation based on the spheric approach. | : The [[media:SphericClass.zip| Sources]]. This class in C# and contains some 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]. | : 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 14:40 26 sep 2011
- In this page we make publicly available a demonstration of a watershed Image Segmentation method based on a hybrid gradient.
- The method has 2 parameters (a,b) that specify the mixture model controlling the of activation of each component of the hybrid gradient. Besides, the method allows the specification of a decision threshold controlling the sensitivity of the method the region mergin.
- For a fast test of the parameters (a,b, threshold). We shared this light application for Windows platforms [media: Hybrid_Watershed_Image Segmentation.zip| application]