DocumentCode
3058767
Title
A rotation, scaling and translation invariant pattern classification system
Author
Yüceer, Cem ; Oflazer, Kemal
Author_Institution
Dept. of Comput. Eng. & Inf. Sci., Bilkent Univ., Ankara, Turkey
fYear
1992
fDate
30 Aug-3 Sep 1992
Firstpage
422
Lastpage
425
Abstract
Presents a hybrid pattern classification system which can classify patterns in a rotation, scaling, and translation invariant manner. The system is based on preprocessing the input image to map it into a rotation, scaling, and translation invariant canonical form, which is then classified by a multilayer feedforward neural net. Results from a number of classification problems are also presented in the paper
Keywords
backpropagation; feedforward neural nets; image processing; backpropagation; canonical form; hybrid pattern classification system; multilayer feedforward neural net; rotation invariance; scaling invariance; translation invariance; Artificial neural networks; Backpropagation algorithms; Data preprocessing; Gravity; Information science; Neural networks; Neurons; Nonhomogeneous media; Pattern classification; Pattern recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 1992. Vol.II. Conference B: Pattern Recognition Methodology and Systems, Proceedings., 11th IAPR International Conference on
Conference_Location
The Hague
Print_ISBN
0-8186-2915-0
Type
conf
DOI
10.1109/ICPR.1992.201808
Filename
201808
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