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Object comparison using PDE‐based wave metric on cellular neural networks
Author(s) -
Szatmári István
Publication year - 2006
Publication title -
international journal of circuit theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.364
H-Index - 52
eISSN - 1097-007X
pISSN - 0098-9886
DOI - 10.1002/cta.361
Subject(s) - metric (unit) , computer science , cellular neural network , hausdorff distance , sensitivity (control systems) , artificial neural network , binary number , object (grammar) , algorithm , pattern recognition (psychology) , theoretical computer science , artificial intelligence , topology (electrical circuits) , mathematics , electronic engineering , operations management , arithmetic , combinatorics , engineering , economics
The paper investigates PDE‐based dynamic phenomena for comparing objects and introduces a spatio‐temporal non‐linear wave metric. This metric is capable of comparing both binary and grey‐scale object pairs in a parallel way. Spatio‐temporal waves are initialized and controlled to explore the quantitative properties of objects. In addition to spatial data, even ‘hidden’, time‐related information is also extracted and used for evaluating differences and similarities. The detailed analysis of the proposed metric shows that this wave‐based approach can outperform well‐known metrics such as Hausdorff and Hamming metrics in selectivity and sensitivity. The approach in question can be efficiently implemented on massively parallel architectures, e.g. on Cellular Neural/Non‐linear Networks (CNN), providing solutions either for real time applications. Copyright © 2006 John Wiley & Sons, Ltd.