Color Object Recognition Using General Fuzzy Min Max Neural Network
نویسندگان
چکیده
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.
منابع مشابه
Speech Recognition Using Modified General Fuzzy Min-Max Neural Network
In this paper, we report the results of Marathi (Language spoken in the state of Maharashtra, India) spoken digit recognition using General Fuzzy Min-Max Neural Network (GFMM NN)[1] and Modified General Fuzzy MinMax Neural Network (MGFMM NN), which is obtained by modifying the transfer function of output layer of GFMM NN.
متن کاملObject Recognition Using Reflex Fuzzy Min-Max Neural Network with Floating Neurons
This paper proposes an object recognition system that is invariant to rotation, translation and scale and can be trained under partial supervision. The system is divided into two sections namely, feature extraction and recognition sections. Feature extraction section uses proposed rotation, translation and scale invariant features. Recognition section consists of a novel Reflex Fuzzy MinMax Neu...
متن کاملAdaptive Color Image Segmentation Using Fuzzy Min-Max Clustering
This paper proposes a novel system for color image segmentation called “Adaptive color image segmentation using fuzzy min-max clustering (ACISFMC)”. The present work is an application of Simpson’s fuzzy min-max neural network (FMMN) clustering algorithm. ACISFMC uses a multilayer perceptron (MLP) like network which perform color image segmentation using multilevel thresholding. Threshold values...
متن کاملPersian Printed Numeral Characters Recognition Using Geometrical Central Moments and Fuzzy Min-Max Neural Network
In this paper, a new proposed system for Persian printed numeral characters recognition with emphasis on representation and recognition stages is introduced. For the first time, in Persian optical character recognition, geometrical central moments as character image descriptor and fuzzy min-max neural network for Persian numeral character recognition has been used. Set of different experiments ...
متن کاملColor Face Segmentation Using a Fuzzy Min-Max Neural Network
This work presents an automated method of segmentation of faces in color images with complex backgrounds. Segmentation of the face from the background in an image is performed by using face color feature information. Skin regions are determined by sampling the skin colors of the face in a Hue Saturation Value (HSV) color model, and then training a fuzzy min-max neural network (FMMNN) to automat...
متن کامل