Content Based Image Retrieval using Color Edge Detection and Discrete Wavelet Transform

Color is one of the most important low-level features used in image retrieval and most content-based image retrievals (CBIR) systems use color as an image features. However, image retrieval using only color features often provide very unsatisfactory results because in many cases, images with similar colors do not have similar content. As the solution of this problem 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 methods. The proposed algorithm generates feature vectors that combines both color and edge features. This paper also uses wavelet transform to reduce the size of the feature vector and simultaneously preserving the content details. The robustness of the system is also tested against query image alterations such as geometric deformations and noise addition etc. Wang's image database is used for experimental analysis and results are shown in terms of precision and recall.