Abstract：
:A visual model for object detection is proposed. In order to make the detection ability comparable with existing technical methods for object detection, an evolution equation of neurons in the model is derived from the computational principle of active contours. The hierarchical structure of the model emerges naturally from the evolution equation. One drawback involved with initial values of active contours is alleviated by introducing and formulating convexity, which is a visual property. Numerical experiments show that the proposed model detects objects with complex topologies and that it is tolerant of noise. A visual attention model is introduced into the proposed model. Other simulations show that the visual properties of the model are consistent with the results of psychological experiments that disclose the relation between figure-ground reversal and visual attention. We also demonstrate that the model tends to perceive smaller regions as figures, which is a characteristic observed in human visual perception.
journal_name
Biol Cybernjournal_title
Biological cyberneticsauthors
Satoh Sdoi
10.1007/s00422-006-0088-2subject
Has Abstractpub_date
2006-09-01 00:00:00pages
259-70issue
3eissn
0340-1200issn
1432-0770journal_volume
95pub_type
杂志文章abstract：:It is shown how field potentials due to neuronal membrane processes can be computed by means of a digital computer system. The essence of the method consists in evaluating a discrete expression for the field potential as a function of membrane potentials. This expression is considered as a three-dimensional convolutio...
journal_title：Biological cybernetics
pub_type： 杂志文章
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pub_type： 杂志文章
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pub_type： 杂志文章
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journal_title：Biological cybernetics
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