Lattice algebra approach to color image segmentation

DOI10.1007/S10851-011-0302-2zbMath1255.68269OpenAlexW1985711602MaRDI QIDQ1932906

Gerhard X. Ritter, Gonzalo Urcid, Juan-Carlos Valdiviezo-N.

Publication date: 22 January 2013

Published in: Journal of Mathematical Imaging and Vision (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10851-011-0302-2

zbMATH Keywords

convex setscolor image segmentationcolor spacesunsupervised clusteringlattice auto-associative memorieslinear mixing modelpixel based segmentation

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Computing methodologies for image processing (68U10) Computer graphics; computational geometry (digital and algorithmic aspects) (68U05)

Cites Work

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• Minimax algebra
• Reconstruction of patterns from noisy inputs using morphological associative memories
• Computational intelligence based on lattice theory.
• Lattice image processing: a unification of morphological and fuzzy algebraic systems
• Active contours without edges
• On Autonomous k-Means Clustering
• Color image segmentation: advances and prospects

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