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In this paper the main challenge lies in the reduction of the semantic gap between low-level features extracted from the image and high-level user semantics. So, the need of CBIR is motivated. The goal of CBIR is to extract visual content of an image automatically, like color, texture, or shape. This project aims to introduce the problems and challenges concerned with the design and the creation of CBIR systems, which is based on a free Database oriented Image retrieval System. With the help of the existing methods, describe a possible solution how to design and implement a task specific descriptor, which can handle the informational gap between a source and images in a Database, making an opportunity for the efficient search hereby. There are lots of algorithms to optimize space and time for the images that are to be retrieved but they are less efficient and also decreasing the quality of images. The main focus of this thesis is to optimize the images efficiently and effectively. This thesis proposed a new technique for images using Intelligent Water Drop optimization for RGB images.

Optimized Content Based Image Retrieval System using Colored Features with IWD