Title :
An evaluation study of traditional and neural network techniques for image processing applications
Author :
Obaidat, M.S. ; Walk, J.V.
Author_Institution :
Dept. of Electr. & Comput. Eng., Missouri-Columbia Univ., Independence, MO, USA
Abstract :
A comparative study of the artificial neural computing and traditional approaches to image processing is performed. The major goal is to determine the usefulness of artificial neural systems (ANSs) for such image processing applications as histogramming and image encoding. The paradigm used was developed from a C programming language model of a perceptron ANS with consideration of backpropagation attributes. It is found that the ANS approach produces results similar to those of traditional techniques
Keywords :
C language; backpropagation; image coding; neural nets; C programming language model; artificial neural computing; artificial neural systems; backpropagation attributes; histogramming; image encoding; image processing applications; neural network techniques; Application software; Associative memory; Backpropagation; Data mining; Image coding; Image processing; Image storage; Multilayer perceptrons; Neural networks; Random access memory;
Conference_Titel :
Circuits and Systems, 1991., Proceedings of the 34th Midwest Symposium on
Conference_Location :
Monterey, CA
Print_ISBN :
0-7803-0620-1
DOI :
10.1109/MWSCAS.1991.252129
