Evaluation of hierarchical watersheds
| Autor: | Deise Santana Maia, Jean Cousty, Silvio Jamil Ferzoli Guimarães, Benjamin Perret |
|---|---|
| Přispěvatelé: | Laboratoire d'Informatique Gaspard-Monge (LIGM), Centre National de la Recherche Scientifique (CNRS)-Fédération de Recherche Bézout-ESIEE Paris-École des Ponts ParisTech (ENPC)-Université Paris-Est Marne-la-Vallée (UPEM), Audio-visual Information Processing Lab [Sao Gabriel] (VIPLAB), Pontifical Catholic University of Minas Gerais [Belo Horizonte] |
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Watershed
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Context (language use) 02 engineering and technology Mathematical morphology computer.software_genre Machine learning 01 natural sciences Electronic mail Set (abstract data type) image analysis 0103 physical sciences 0202 electrical engineering electronic engineering information engineering mathematical morphology 010306 general physics image segmentation Mathematics Hierarchy business.industry Hierarchy of partitions Image segmentation watershed hierarchy quasi-flat zones hierarchy Object (computer science) Computer Graphics and Computer-Aided Design [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV] 020201 artificial intelligence & image processing watershed segmentation Artificial intelligence Data mining business computer Software |
| Zdroj: | IEEE Transactions on Image Processing IEEE Transactions on Image Processing, Institute of Electrical and Electronics Engineers, 2018, 27 (4), pp.1676-1688. ⟨10.1109/TIP.2017.2779604⟩ |
| ISSN: | 1057-7149 |
| DOI: | 10.1109/TIP.2017.2779604⟩ |
| Popis: | International audience; This article aims to understand the practical features of hierarchies of morphological segmentations, namely the quasi-flat zones hierarchy and watershed hierarchies, and to evaluate their potential in the context of natural image analysis. We propose a novel evaluation framework for hierarchies of partitions designed to capture various aspects of those representations: precision of their regions and contours, possibility to extract high quality horizontal cuts and optimal non-horizontal cuts for image segmentation, and ease of finding a set of regions representing a semantic object. This framework is used to assess and to optimize hierarchies with respect to the possible pre-and post-processing steps. We show that, used in conjunction with a state-of-the art contour detector, watershed hierarchies are competitive with complex state of the art methods for hierarchy construction. In particular, the proposed framework allows us to identify a watershed hierarchy based on a novel extinction value, the number of parent nodes, that outperforms the other hierarchies of morphological segmentations. This coupled with the fact that watershed hierarchies satisfy clear global optimality properties and can be computed efficiently on large data, make them valuable candidates for various computer vision tasks. |
| Databáze: | OpenAIRE |
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