An innovative medical image retrieval is proposed to extract low-level image texture
features. These low level texture features were extracted directly using Modified Discrete …

With the rapid development and wide application of medical imaging technology, explosive
volumes of medical image data are produced every day all over the world. As such, it …

Problem statement: Recently, there has been a huge progress in collection of varied image
databases in the form of digital. Most of the users found it difficult to search and retrieve …

Content-based image retrieval (CBIR) is the most commonly used method for searching
large-scale medical image databases. Images are generally retrieved on the basis of either …

The ever-increasing popularity of the use of larger-volume image database in various
applications, it is an imperative to build an efficient retrieval system to browse through the …

An obvious way to describe texture is their statistical properties. The technique involves
statistically sampling the way certain gray levels occur in relation to other gray levels. So …

Texture characteristic is an important attribute of medical images, and has been applied in
many medical image applications. This paper proposes a simple approach to employ the …

This paper presents a method for endoscopic image retrieval based on color–texture
correlogram and Generalized Tversky's Index (GTI) model. First we define a new image …

Image retrieval is a specialized search to find images of interest. User may give a keyword,
sketch or image itself to image search engine to retrieve back relatively similar images from …

Effective Content-Based Image Retrieval (CBIR) is based on efficient low level features
extraction for indexing and on effective query image matching with indexed images for …