Color Object Recognition Using General Fuzzy Min Max Neural Network

Abstract

-A hybrid approach based on Fuzzy Logic and neural networks with the combination of the classic Hu & Zernike moments joined with Geodesic descriptors is used to keep the maximum amount of information that are given by the color of the image. These moments are calculated for each color level and geodesic descriptors are applied directly to binary images to get information about the general shape of the object. The extracted features are given as input to the General Fuzzy Min-Max Neural Network architecture. General Fuzzy Min-Max Neural Network is The fusion of clustering and classification resulted in an algorithm that can be used as pure clustering, pure classification, or hybrid clustering classification.