Rotation Invariant Content-Based Image Retrieval System

The emergence of multimedia technology and the rapid growth in the number and type of multimedia assets controlled by several entities, yet because the increasing range of image and video documents showing on the Internet, have attracted vital analysis efforts in providing tools for effective retrieval and management of visual data. So the need for image retrieval system arose. Out of many existing systems “ROTATION INVARIANT CONTENT-BASED IMAGE RETRIEVAL SYSTEM” is the most efficient and accurate one. Effective texture feature is an essential component in any CBIR system. In the past, spectral features like Gabor and Wavelet have shown superior retrieval performance than most statistical and structural options. Recent researches on multi-resolution analysis have found that curvelet captures texture properties like curves, lines and edges with additional accuracy than Gabor filters. However, the texture feature extracted using curvelet transform is not rotation invariant. This can degrade its retrieval performance considerably, particularly in cases where there are many similar images with different orientations. We analyses the curvelet transform and derives a useful approach to extract rotation invariant curvelet features. The new system which uses curvelet transform for extracting texture features includes rotation invariant.