Attention choice on quotient space composition for automatic target image segmentation

The authors present a novel method for image segmentation using neocognitron neuron model with diffusion and concentration properties controlled by quotient structure. The contributions of this paper are two fold: (1) In order to remark upon the relationship between the components of an image corres...

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Published inIGARSS 2000. IEEE 2000 International Geoscience and Remote Sensing Symposium. Taking the Pulse of the Planet: The Role of Remote Sensing in Managing the Environment. Proceedings (Cat. No.00CH37120) Vol. 2; pp. 666 - 668 vol.2
Main Author Guan Zequn
Format Conference Proceeding
LanguageEnglish
Published IEEE 2000
Subjects
Automatic control
Image analysis
Image segmentation
Image storage
Information processing
Layout
Merging
Neurons
Predictive models
Remote sensing
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Summary:The authors present a novel method for image segmentation using neocognitron neuron model with diffusion and concentration properties controlled by quotient structure. The contributions of this paper are two fold: (1) In order to remark upon the relationship between the components of an image corresponding to the patches, which give the typed association of objects, the notion of quotient space composition and projection is introduced. This provides the advantage that the new patches for image segmentation may be created by merging the patches from the above level of the quotient space. (2) The hierarchical structure of neocognitron for the attention choice is adjusted with the variance of scenes by the process of the diffusion and concentration. The validity of our approach is demonstrated by an example in image analysis.
ISBN:0780363590
9780780363595
DOI:10.1109/IGARSS.2000.861665