الفهرس 
CHAPTER 1 - IntroductionOnly 14 pages are availabe for public view
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Abstract
Digital images are an increasingly important class of data, especially as computers become more usable with greater memory and communication capacities. As the demand for digital images increases, the need to store and retrieve images in an intuitive and efficient manner arises. Hence, the field of content-based image retrieval (CBIR) focuses on intuitive and efficient methods for retrieving images from databases based solely on the content contained in the images. This dissertation develops an information theoretic view of images that improves the speed of retrieval of images. this these consist of five chapters
1 - Introduction :-
Digital images are used throughout science, engineering, business, and personal computing. There are several reasons for the proliferation of images throughout general computer usage. The demilitarization of imaging and satellite technology has made it possible to capture data in high resolution formats and from almost any region of the world. The emergence and explosive use of the World Wide Web (WWW) as a global network allows people to gather and share images en masse indeed . The impetus to merge television, entertainment, and computing technology into a cohesive platform is a forcing function for the miniaturization, low cost fabrication, and increased capacity of memory and secondary storage devices. As the popularity of digital images grows, so does the need to organize, store, and retrieve images from collections or databases.
2- Edge Derection:-
Edge detection is a fundamental tool in image processing and computer vision, particularly in the areas of feature detection and feature extraction, which aim at identifying points in a digital image at which the image brightness changes sharply or, more formally, has discontinuities. The same problem of finding discontinuities in 1D signals is known as step detection. Edges are significant local changes of intensity in an image. Edges typically occur on the boundary between two different regions in an image.
3-Shapes:-
Recent years have seen an enormous increase in the number of images captured by digital cameras. The ease and convenience of capturing digital images and transmitting them between digital cameras and image databases is a contributing factor to the immense growth of image databases. These databases cover a wide range of applications, including military, environmental, astronomy, transportation, aviation, medical and multimedia. The storage format of the image data is relatively standardized; however, the effective retrieval of images from such databases remains a significant challenge.
4- The Local Binary Pattern.
Texture can be broadly defined as the visual or tactile surface characteristics and appearance of something. Textures can consist of very small elements like sand, or of huge elements like stars in the Milky Way. Texture can also be formed by a single surface via variations in shape, illumination, shadows, absorption and reflectance. Just about anything in the universe can appear as a texture if viewed from a proper distance. However, it is important to recognize that “texture regions give different interpretations at different distances and at different degrees of visual attention” (Chaudhuri et al. 1993). A single star, viewed from a distance, is not a texture, but its surface might be.
5- Content Based Image Retrieval and Information Theory
Information theory is a branch of applied mathematics, electrical engineering, and computer science involving the quantification of information. The field of CBIR research is incomplete with respect to user analysis.
6- Proposed Algorithms Image searching is one of the most important services that need to be supported by such systems. In these systems, image processing algorithms (usually automatic) are used to extract feature vectors that represent image properties such as color,texture, and shape.
7- Experimental Results.
The performance of a Content Based Image Retrieval (CBIR) system is inherently constrained by the features adopted to represent the images in the database.