A Spatially Constrained Generative Model and an EM Algorithm for Image Segmentation - Diplaros, A.; Vlassis, N.; Gevers, T. (IEEE transactions on neural networks, 2007)
Keywords: Algorithms; Applied sciences; Artificial Intelligence; Bound optimization; Clustering algorithms; Computer science; control theory; systems; Computer Simulation; Connectionism. Neural networks; Constraints; Exact sciences and technology; expectation-maximization (EM) algorithm; Hidden Markov models; hidden Markov random fields (MRFs); Image color analysis; Image edge detection; Image Enhancement - methods; Image Interpretation, Computer-Assisted - methods; Image segmentation; Informatics; Intelligent sensors; Intelligent systems; Iterative algorithms; Labels; Likelihood Functions; Mathematical models; Models, Statistical; Pattern Recognition, Automated - methods; Pattern recognition. Digital image processing. Computational geometry; Pixel; Pixels; spatial clustering; Cluster analysis; Mixed distribution; Markov process; expectation-maximization (EM) algorithm; Lower bound; hidden Markov random fields (MRFs); Probabilistic approach; Similarity; Image processing; Prior distribution; spatial clustering; Neural network; Modeling; Competitive algorithms; Optimization; Image segmentation; Gaussian process; Classification; Hidden Markov model; Log file; EM algorithm; Bound optimization