ABSTRACT:

Digital Image Processing domain is constantly contributing to make digital era more concise. Specifically Image Retrieval is the trending research area now-a-days. The main problem is, with the increasing volume of digital data the complexity of searching a specific image and retrieving the particular data associated with it is increasing. In recent years the content based image retrieval system has been developing at enormous speed. This paper color , gray level co-occurrence and histogram features are obtain better retrieval efficiency from large database using these feature vectors near about similarly matched images are retrieved. We have retrieved using Euclidian distance and ANN, among of both ANN Shows better result compare to Euclidian Distance based image retrieval.

INTRODUCTION:

Very massive collections of images are growing quickly because of arrival of cheaper storage devices and also the internet. Finding an image from a huge set of images is very challenging task. One solution to this problem is to label images manually. But it is too expensive, time consuming and not feasible for several applications. Moreover, the labeling process depends on the semantic accuracy in describing the image. Therefore, many content based image retrieval systems are developed to extract low levels features for describing the image content [1].
In free browsing method one have to go through the entire database till the required data sample is found. Next in the concept based method which is also termed as the text based retrieval method some predefined data have been attached with image or audio file and by comparing that data finally the retrieval is carried out. Lastly in the content based retrieval method the search of specific content of the information is carried out and then the main image is extracted. The technologies present mostly uses the concept based and the content based image retrieval scheme. The attachment of predefined data to a typical data file is a tedious job as, it requires human intervention also so much time consuming.
In the content based image retrieval method a typical feature is taken into consideration. Feature can be defined as an attribute that can capture a definite visual property of an image.