Title :
A fuzzy classification system for analysis of polymer spectra using fast wavelet transforms
Author :
Wirth, Georg ; Bale, C.F. ; Mlynski, Dieter A.
Author_Institution :
Inst. fur Theor. Elektrotech. und Messtech., Karlsruhe Univ., Germany
Abstract :
We propose an efficient strategy for qualitative analysis of measured polymer spectra based on fast wavelet transforms and fuzzy set theory. First a wavelet transform is applied to the measured data acting as a feature extractor. Thus huge data sets are enormously compressed and only a few typical features (wavelet coefficients) locating the spectra peaks remain for the identification process. Then, a fuzzy classification algorithm separates different spectra into various clusters thus giving a qualitative interpretation of the ingredients due to calculated membership values. For that we implemented a fuzzy c-means algorithm, a fuzzy Kohonen cluster algorithm and special rule based approach with fuzzy if-then rules
Keywords :
feature extraction; fuzzy set theory; infrared spectra; infrared spectroscopy; knowledge based systems; pattern classification; polymers; self-organising feature maps; spectral analysis; spectroscopy computing; wavelet transforms; IR spectroscopy; fast wavelet transforms; feature extractor; fuzzy Kohonen cluster algorithm; fuzzy c-means algorithm; fuzzy classification algorithm; fuzzy classification system; fuzzy if-then rules; fuzzy set theory; identification process; measured data; measured polymer spectra; membership values; polymer spectra analysis; qualitative analysis; rule based approach; wavelet coefficients; Classification algorithms; Clustering algorithms; Data mining; Feature extraction; Fuzzy set theory; Fuzzy systems; Polymers; Wavelet analysis; Wavelet coefficients; Wavelet transforms;
Conference_Titel :
Image Processing, 1996. Proceedings., International Conference on
Conference_Location :
Lausanne
Print_ISBN :
0-7803-3259-8
DOI :
10.1109/ICIP.1996.561061
