DocumentCode :
2672422
Title :
A multiresolution hybrid neuro-Markovian image modeling and segmentation
Author :
Wiliñski, Piotr ; Solaiman, Basel ; Hillion, Alain ; Czarnecki, Witold
Author_Institution :
Ecole Nat. Superieure des Telecommun. de Bretagne, Brest, France
Volume :
3
fYear :
1996
fDate :
16-19 Sep 1996
Firstpage :
951
Abstract :
A new textured image model is proposed. This model is described by means of a neuro-Markovian hybrid approach using a Kohonen map and a hidden Markov model (HMM). Each state of the HMM describes one resolution level in the image. The change of the state corresponds to the change of image analysis resolution level. The HMM observation space is composed of clusters which are estimated using a Kohonen map. The second role of the Kohonen algorithm is to achieve a segmentation which is done in parallel with the one proceeded by a Viterbi algorithm. The results given by the both algorithms present some complementarity
Keywords :
hidden Markov models; image classification; image resolution; image segmentation; image texture; parameter estimation; self-organising feature maps; HMM observation space; Kohonen map; clusters; contextual classification; hidden Markov model; image segmentation; multiresolution image analysis; neuro-Markovian hybrid approach; textured image model; Clustering algorithms; Hidden Markov models; Image analysis; Image resolution; Image segmentation; Image texture analysis; Information analysis; Pixel; Signal processing algorithms; Viterbi algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 1996. Proceedings., International Conference on
Conference_Location :
Lausanne
Print_ISBN :
0-7803-3259-8
Type :
conf
DOI :
10.1109/ICIP.1996.560957
Filename :
560957
Link To Document :
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