Title | ||
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Reconstruction with criterion from labeled markers: new approach based on the morphological watershed. |
Abstract | ||
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The goal of image segmentation is to partition an input image into a set of regions. In mathematical morphology, the reconstruction of images from markers has proven to be useful in morphological filtering and image segmentation. The utilization of a criterion in the problem of the image reconstruction from an image marker has been partially treated elsewhere. We further investigate this idea and extend it to the problem of image reconstruction from labeled markers by proposing a new method based on the "watershed" transformation as an alternative in image segmentation. The image gradient is considered as a topographic relief that is flooded (similarly as in a nor-mal watershed). However, a criterion is added in this reconstruction process that enables the flexibility to separate structures of interest. Following the flooding analogy on topographic reliefs, this flooding process is limited to certain zones to control the recovering process of structures shapes. Experimental results are provided. A comparison with a viscous watershed is performed to show the differences between them. The technique is applied mainly in the biomedical do-main, although the technique can generally be applied to other areas. (C) 2010 SPIE and IS&T. [DOI: 10.1117/1.3491494] |
Year | DOI | Venue |
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2010 | 10.1117/1.3491494 | JOURNAL OF ELECTRONIC IMAGING |
Keywords | Field | DocType |
particles,image reconstruction,image restoration,integral transforms,image segmentation,mathematical morphology | Computer vision,Image gradient,Scale-space segmentation,Pattern recognition,Feature detection (computer vision),Computer science,Image texture,Segmentation-based object categorization,Image segmentation,Artificial intelligence,Image restoration,Morphological gradient | Journal |
Volume | Issue | ISSN |
19 | 4 | 1017-9909 |
Citations | PageRank | References |
4 | 0.44 | 15 |
Authors | ||
5 |
Name | Order | Citations | PageRank |
---|---|---|---|
Damián Vargas-Vázquez | 1 | 28 | 2.27 |
José Crespo | 2 | 126 | 24.90 |
Victor Maojo | 3 | 333 | 53.22 |
José Gabriel Ríos Moreno | 4 | 6 | 0.86 |
Mario Trejo Perea | 5 | 6 | 0.86 |