A neural network model for the perception of occluded surfaces from subjective contours

Author

Jeong, Eunhwa ; Hong, Keongho ; Kim, Wookhyun

Author_Institution

Dept. of Comput. Sci., Chonan Univ., South Korea

Volume

1

fYear

1999

fDate

1999

Firstpage

162

Abstract

A neural network model for the perception of occluded surfaces from subjective contours has been presented. This model employs an important two-stage process of the induced stimuli extraction system (ISES) and subjective surfaces perception system (SSPS). The former system extracts the induced stimuli for the perception of subjective surfaces, and the latter forms the subjective surfaces from the induced stimuli. The proposed model is based on the mechanism of feature extraction found in the visual pathway. The results of the experiment showed that the proposed model was successful not only in extracting the induced stimuli for the perception of subjective contours, but also in perceiving the subjective surface from the induced stimuli

Keywords

edge detection; feature extraction; neural nets; experiment; feature extraction; image contours; induced stimuli extraction system; neural network model; occluded surfaces perception; subjective contours; subjective surfaces; subjective surfaces perception system; two-stage process; visual pathway; Computational modeling; Computer networks; Computer science; Data mining; Electronic mail; Feature extraction; Foot; Neural networks; Photoreceptors; Retina;

fLanguage

English

Publisher

ieee

Conference_Titel

TENCON 99. Proceedings of the IEEE Region 10 Conference

Conference_Location

Cheju Island

Print_ISBN

0-7803-5739-6

Type

conf

DOI

10.1109/TENCON.1999.818375

Filename

818375