A shape classifier based on Hopfield-Amari network

A shape classifier based on Hopfield-Amari network

The representation and recognition of a planar shape based on contour information is an important issue in computer vision. We propose a method for extracting the main features of a contour using the curve bend function (CBF), which can be used to characterize the contour completely. A Hopfield-Amar...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Hauptverfasser: Fu, A.M.N., Hong Yan
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Associative memory
Computer vision
Counting circuits
Data mining
Feature extraction
Hopfield neural networks
Pattern analysis
Pattern recognition
Power system reliability
Shape
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Beschreibung
Zusammenfassung:The representation and recognition of a planar shape based on contour information is an important issue in computer vision. We propose a method for extracting the main features of a contour using the curve bend function (CBF), which can be used to characterize the contour completely. A Hopfield-Amari network is built based on the CBF description to perform classification of planar shapes. The experimental results demonstrate that the proposed system is powerful and reliable for solving shape recognition problems.
DOI:10.1109/ICNN.1996.548961