A Sravani

Image Retrieval & Classification Based on Selective Feature Extraction A Sravani

In this digital era with the availability of enormous digital data on the Internet, the users have to search for different means of retrieving suitable data from the unorganized data. Classification is one such technique which has helped the researchers worldwide to narrow their search. Among the data available due to the increase in digital technologies availability of multimedia data is rapidly increasing day by day. To retrieve the required data (images) many researchers have given algorithms or methods to retrieve images among which image classification is one. It has played an important role in many applications like Medicine, Photogrammetric, and Computer Vision etc. In this project, an attempt is made to design a methodology for an efficient image classification system by extracting 50 features followed by image classification by incorporating different classification techniques. This project also deals with retrieving a new image instance which is not present in the training data set followed by image classification. A comparison is done between the classification techniques used and experimental results conducted on 1150 different images belonging to 17 different categories