NDLI: Extracting symmetry axes: a neural network model

Content Provider	IEEE Xplore Digital Library
Author	Fukushima, K. Kikuchi, M.
Copyright Year	2004
Description	Author affiliation: Sch. of Media Sci., Tokyo Univ. of Technol., Japan (Fukushima, K.)
Abstract	This paper proposes a neural network model that extracts axes of symmetry from visual patterns. The input patterns can be line drawings, plane figures or gray-scaled natural images taken by CCD cameras. The model is a multi-layered network. It has an input layer, a contrast-extracting layer, edge-extracting layers (an S-cell layer and a C-cell layer), and layers extracting symmetry axes. These layers are connected in a cascade in a hierarchical manner. The model extracts oriented edges from the input image first, and then tries to extract axes of symmetry. To reduce the computational cost, the model checks conditions of symmetry, not directly from the oriented edges, but from a blurred version (low-resolution responses covering a large area) of them. The use of blurred signals endows the network with a large tolerance to deformation of input patterns, too.
Starting Page	321
Ending Page	326
File Size	426469
Page Count	6
File Format	PDF
ISBN	0780383591
ISSN	10987576
DOI	10.1109/IJCNN.2004.1379921
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-07-25
Publisher Place	Hungary
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neural networks Computational efficiency Electronic mail Computational modeling Paper technology Charge coupled devices Charge-coupled image sensors Testing Computer networks Spatial filters
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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