An Enhance Image Retrieval of User Interest - Survey

In recent years, image retrieval process has increased artistically. An image retrieval system is a process for searching and retrieving images from large amount of the image dataset. Increase the accuracy of image retrieval, content based image retrieval system (CBIR) and text-based image retrieval system (TBIR) based on interactive genetic algorithm (IGA) and SVM is proposed. Color, texture and edge have been the primitive low level image descriptors in content based image retrieval systems. In this paper we discover a system which splits the search process into two stages. In the query specify approach the feature descriptors of a query image we re-extracted and then used to check the similarity between the query image and those images which is in database. In the evolution stage, the most relevant images were retrieved by using the Interactive genetic algorithm. IGA help the users to retrieve the images that are most relevant to the users' need and SVM will rank the image as their title and as par time of search. So that user can get search image as par their requirements.