Distributed Component Forests in 2-D
| Autor: | Michael H. F. Wilkinson, Simon Gazagnes |
|---|---|
| Přispěvatelé: | Centre for Data Science and Systems Complexity (DSSC), Intelligent Systems |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Scale (ratio)
Computer science business.industry Pattern recognition 02 engineering and technology Mathematical morphology 01 natural sciences Image (mathematics) Artificial Intelligence Component (UML) 0103 physical sciences 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computer Vision and Pattern Recognition Artificial intelligence business Tera 010303 astronomy & astrophysics Software |
| Zdroj: | International Journal of Pattern Recognition and Artificial Intelligence, 33(11 SI):1940012 |
| ISSN: | 0218-0014 |
| DOI: | 10.1142/s0218001419400123 |
| Popis: | The standard representations known as component trees, used in morphological connected attribute filtering and multi-scale analysis, are unsuitable for cases in which either the image itself or the tree do not fit in the memory of a single compute node. Recently, a new structure has been developed which consists of a collection of modified component trees, one for each image tile. It has to-date only been applied to fairly simple image filtering based on area. In this paper, we explore other applications of these distributed component forests, in particular to multi-scale analysis such as pattern spectra, and morphological attribute profiles and multi-scale leveling segmentations. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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