Content Based Image Retrieval Using Different Techniques

Color is one of the most imperative low-level features used in image retrieval and most content-based image retrievals (CBIR) schemes use color as an image features. However, imagere possession using only color features often provide very inadequate outcomes because in many cases, images with comparable colors do not have similar content. As the clarification of thisproblem this paper describes a novel algorithm for Content Based Image Retrieval (CBIR) based on Color Edge Detection and Discrete Wavelet Transform (DWT). This method is different from the existing histogram based techniques. Theproposed algorihm generates feature vectors that conglomerate both color and edge features. This documents also uses wavelet transform to diminish the size of the feature vector and concurrently conserving the content details. The forcefulness ofthe structure is also tested against query image adjustments such as geometric distortions and noise calculation etc. Wang's image database is used for tentative study and results are presented in terms of precision and recall.