Content Based Image Retrieval Based on KNN Classification and Feature Selection Using ANT Colony Optimization

Content-based image retrieval systems retrieve images from a database that are determined to be similar to a query image based only on features extracted from the images. Some methods are defined to improve the efficiency and effectiveness of color-based retrieval. To test the theory using a collection of color images and query images. Our empirical results are very encouraging. This paper focuses on color-based image retrieval. Here main aim is on how to retrieve the images from large database. Generally in huge databases there are large numbers of images with the same name. In this method it retrieves the images with same name, but in this method it retrieves the images based on the content in the image and it also show the comparison between present image in the database with the target image using ant colony optimization and KNN algorithm we are searching for. This is fast and efficient method for retrieving the exact images from huge databases.