Physically-based active shape models
| Autor: | A. Garrido, N. Pérez de la Blanca |
|---|---|
| Rok vydání: | 1998 |
| Předmět: |
business.industry
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Initialization Image processing Hough transform law.invention Orthogonal coordinates Artificial Intelligence law Active shape model Signal Processing Canonical form Segmentation Computer vision Computer Vision and Pattern Recognition Artificial intelligence Noise (video) business Software ComputingMethodologies_COMPUTERGRAPHICS Mathematics |
| Zdroj: | Pattern Recognition. 31:1003-1017 |
| ISSN: | 0031-3203 |
| DOI: | 10.1016/s0031-3203(97)00125-8 |
| Popis: | In this paper we describe a new approach for 2-D object segmentation using an automatic method applied on images with problems as partial information, overlapping objects, many objects in a single scene, severe noise conditions and locating objects with a very high degree of deformation. We use a physically-based shape model to obtain a deformable template, which is defined on a canonical orthogonal coordinate system. The proposed methodology works starting from the output of an edge detector, which is processed to automatically obtain an approximation of the shape. The final estimation of the shapes is obtained fitting a deformable template model, which is defined on a learned surface of deformation. Results from biological images are presented. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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