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Segmentation of heterogeneous blob objects through voting and level set formulation
- Source :
- Pattern Recognition Letters. 28:1781-1787
- Publication Year :
- 2007
- Publisher :
- Elsevier BV, 2007.
-
Abstract
- Blob-like structures occur often in nature, where they aid in cueing and the pre-attentive process. These structures often overlap, form perceptual boundaries, and are heterogeneous in shape, size, and intensity. In this paper, voting, Voronoi tessellation, and level set methods are combined to delineate blob-like structures. Voting and subsequent Voronoi tessellation provide the initial condition and the boundary constraints for each blob, while curve evolution through level set formulation provides refined segmentation of each blob within the Voronoi region. The paper concludes with the application of the proposed method to a dataset produced from cell based fluorescence assays and stellar data.
- Subjects :
- business.industry
Computer science
media_common.quotation_subject
Pattern recognition
Image processing
Image segmentation
Computer Science::Computational Geometry
Article
Level set
Artificial Intelligence
Voting
Signal Processing
Initial value problem
Segmentation
Computer vision
Computer Vision and Pattern Recognition
Artificial intelligence
Centroidal Voronoi tessellation
Voronoi diagram
business
Software
media_common
Subjects
Details
- ISSN :
- 01678655
- Volume :
- 28
- Database :
- OpenAIRE
- Journal :
- Pattern Recognition Letters
- Accession number :
- edsair.doi.dedup.....03ca6d8e8a5d2a46560ef9c3d653672d