A Content Based Image Retrieval Using Soft Computing Technique

Abstract

The CBIR tends to index and retrieve images based on their visual content. CBIR avoids many problems associated with traditional ways of retrieving images by keywords. Thus, a growing interest in the area of CBIR has been established in recent years. The performance of a CBIR system mainly depends on the particular image representation and similarity matching function employed. The CBIR tends to index and retrieve images based on their visual content. CBIR avoids many problems associated with traditional ways of retrieving images by keywords. Thus, a growing interest in the area of CBIR has been established in recent years. The performance of a CBIR system mainly depends on the particular image representation and similarity matching function employed. So a new CBIR system is proposed which will provide accurate results as compared to previous developed systems. Soft technique will be used in this system. Based Image Retrieval system which evaluates the similarity of each image in its data store to a query image in terms of various visual features and return the image with desired range of similarity. To develop and implement an efficient feature extraction NN to extract features according to data set using Auto calculate the feature weight by neural network. The precision and recall graph in gui according to the retrieved contents of the images from the datasets. To Apply back propagation or feed forward algorithm for neural network classification. To calculate cross correlation and apply regression model for feature matching.