A Proposed Method for Image Retrieval Using Normalized Euclidean Distance and Coefficient Analysis

The paper, proposed a novel method based on normalized Euclidean distance using application of discrete wavelet transform and histogram bins intensity measurement, which is then tied to a parameterized framework for content-based image retrieval. Image retrieval is an active research area in image processing, pattern identification, and computer visualization. The discrete wavelet transform captures both frequency and location information and make image retrieval efficient. It further facilitates to incorporate recent research work on feature based coefficient distributions. The resemblance of images depends on the feature illustration. We demonstrate the applicability of the proposed method in the context of color texture retrieval on different image databases and compare retrieval performance to a collection of state-of-the-art approaches in the area to improve the results.