%0 Journal Article
%T IMAGE CLASSIFICATION USING ARTIFICIAL NEURAL NETWORKS: AN EXPERIMENTAL STUDY ON COREL DATABASE
%A DHANYA BIBIN and PUNITHA P
%J International Journal of Machine Intelligence
%D 2011
%I Bioinfo Publications
%X In this paper high-level image classes are inferred from low-level image features like color and shape features with the help of artificial neural network. Back propagation neural network algorithm is used for integrating knowledge from low-level image features and classify the images into high level concepts / semantic classes. The classifier is evaluated on a database of 1000 images from COREL database. The experimental results show that the accuracy using back propagation neural network algorithm to classify COREL images ranges between 80.5% to 88.6%.
%K CBIR
%K Image classification
%K Artificial neural networks(ANN)
%K COREL database
%K Color histogram
%K Color moments
%K Color coherence vector
%K Edge direction histogram
%U http://www.bioinfo.in/uploadfiles/13257536853_4_9_IJMI.pdf