Graph-Based Semantic Segmentation for 3D Digital Images
| Autor: | Cosmin Stoica Spahiu, Liana Stanescu, Daniel Costin Ebanca, Dumitru Dan Burdescu, Marius Brezovan |
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| Rok vydání: | 2017 |
| Předmět: |
Image formation
Morphological gradient Computer science ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Scale-space segmentation Image processing 02 engineering and technology Digital image Image texture Minimum spanning tree-based segmentation Digital image processing 0202 electrical engineering electronic engineering information engineering Segmentation Computer vision Image gradient Image restoration ComputingMethodologies_COMPUTERGRAPHICS Feature detection (computer vision) Segmentation-based object categorization business.industry Binary image 020206 networking & telecommunications Pattern recognition Image segmentation Automatic image annotation Region growing 020201 artificial intelligence & image processing Artificial intelligence Range segmentation business Connected-component labeling |
| Zdroj: | AINA Workshops |
| DOI: | 10.1109/waina.2017.69 |
| Popis: | Graph-based segmentation is gaining popularity among the many approaches in performing image segmentation, primarily due to its ability in reflecting global image properties. The most fundamental challenge in segmentation algorithm is to precisely define the volumetric extent of some object, which may be represented by the union of multiple regions. We developed a unified framework for volumetric image segmentation and contour extraction that uses a virtual tree-hexagonal structure defined on the set of the image voxels. The most important characteristic of using a virtual tree-hexagonal network over the initial image voxels is that it reduces the execution time and the memory space used, without losing the initial resolution of the image. |
| Databáze: | OpenAIRE |
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