Title :
Neuro-fuzzy system for adaptive multilevel image segmentation
Author :
Boskovitz, Victor ; Guterman, Hugo
Author_Institution :
Dept. of Electr. & Comput. Eng., Ben-Gurion Univ. of the Negev, Beer-Sheva, Israel
Abstract :
An auto-adaptive neuro-fuzzy segmentation architecture is presented. The system consists of a multilayer perceptron (MLP) network that performs adaptive thresholding of the input image using labels automatically preselected by a fuzzy clustering technique. The proposed architecture is feedforward, but unlike the conventional MLP the learning is unsupervised. The output status of the network is described as a fuzzy set. Fuzzy entropy is used as a measure of the error of the system
Keywords :
adaptive signal processing; entropy; error analysis; feedforward neural nets; fuzzy neural nets; fuzzy set theory; image segmentation; unsupervised learning; adaptive multilevel image segmentation; adaptive thresholding; auto-adaptive neuro-fuzzy segmentation architecture; error; feedforward; fuzzy clustering; fuzzy entropy; fuzzy set; input image; multilayer perceptron; output status; unsupervised learning; Adaptive systems; Entropy; Fuzzy neural networks; Fuzzy sets; Fuzzy systems; Image segmentation; Multi-layer neural network; Multilayer perceptrons; Neural networks; Pixel;
Conference_Titel :
Electrical and Electronics Engineers in Israel, 1996., Nineteenth Convention of
Conference_Location :
Jerusalem
Print_ISBN :
0-7803-3330-6
DOI :
10.1109/EEIS.1996.566931
