Title :
System of associative relationships (SOAR)
Author :
Ozturk, Yusuf ; Abut, Hüseyin
Author_Institution :
Dept. of Electr. & Comput. Eng., San Diego State Univ., CA, USA
Abstract :
We propose a new architecture for texture classification based on pair-wise pixel associations as an extension of the multivalued recursive network (MAREN) architecture. Maybe more critically we propose a novel similarity measure and classification algorithm to be used with this network. The proposed fidelity criterion has been observed to be tightly coupled with the ubiquitous mean-square error (MSE) distance measure. Both SOAR and MAREN structures can be considered as an extension of the associative memory concept frequently used in neural networks. Our proposed similarity measure is based on the principle of directional divergence of interpixel relationships in a given texture and promises a number of advantages over the MSE measure. The SOAR is discussed within the framework of a texture classification problem, but we believe it would be very easy to extend it to other applications where the interpixel relationship is the primary focus.
Keywords :
content-addressable storage; image classification; image texture; learning (artificial intelligence); least mean squares methods; neural net architecture; recurrent neural nets; MSE distance measure; associative memory; classification algorithm; directional divergence; fidelity criterion; interpixel relationships; learning algorithm; mean-square error; multivalued recursive network architecture; pair-wise pixel associations; similarity measure; system of associative relationships; texture classification; Associative memory; Classification algorithms; Computer architecture; Electronic mail; Focusing; Image processing; Multidimensional systems; Neural networks; Pixel; Shape;
Conference_Titel :
Signals, Systems & Computers, 1997. Conference Record of the Thirty-First Asilomar Conference on
Conference_Location :
Pacific Grove, CA, USA
Print_ISBN :
0-8186-8316-3
DOI :
10.1109/ACSSC.1997.680529