International Journal of Application or Innovation in Engineering & Management (IJAIEM)
Widespread cardinality of images and paintings has made traditional keyword based search, an inefficient method for retrieval of required input image data. When the users input an image into the database, then Content-Based Image Retrieval (CBIR) system gets the similar images from a large database for that query image. Implementation of CBIR can be done using features like color, texture and shape; these features are called low level features. In this paper, using a feed-forward back propagation neural network, classification of images in CBIR system is proposed. At first, the neural network is trained about the features of images in the database.