Computers are beginning to replace photographic archives as the preferred form of repository. Computer based images repositories provides a flexible that cannot be attained with collection of printed images. Recently there has been as explosion in the number of images available to computer users. As this number increases, users require more sophisticated methods of retrieval. The area of content-based image retrieval is a hybrid research area that requires knowledge of both computer vision and of database systems. Large image databases are being collected, and images from these collections made available to users in advertising, marketing, entertainment, and other areas where images can be used to enhance the product. These images are generally organized loosely by category, such as animals, natural scenes, people, and so on. Content-based retrieval systems utilize measures that are based on low-level attributes of the image itself, including color histograms, color composition, and texture. State-of-the-art research focuses on more powerful measures that can find regions of an image corresponding to known objects that users wish to retrieve. There has been some success in finding human faces of different selected sizes, human bodies, horses, zebras and other texture animals with known patterns, and such backgrounds as jungles, water, and sky. In this paper I presented SIMBA, Content based image retrieval system performing queries based on image appearance. Considering absolute object position irrelevant for image similarly here and therefore propose to use invariant feature. Based on general construction method (interaction over the transformation group) Deriving invariant feature histograms that are strongly influenced by color and textural features that are robust to illumination change .By a weighted combination of these feature the user can adapt the similarity measure according to his needs thus improving the retrieval result considerably .The feature extraction does not require any manual interaction, so that it might be used for fully automatic image databases.