Abstract

With increasing the popularity of World Wide Web, storing digital contents increases enormously, in that case, it is important to implement convenient information systems which manage the collections of these digital contents efficiently. This paper concentrates on hastening techniques for efficient retrieval of images. Content-Based Image Retrieval (CBIR) systems are used by common approaches. These systems support retrieving similar images depend on content properties (e.g., color, shape, and texture) by retrieving automatically similar images to a pattern or user-defined specification. The CBIR generally used in several applications by applying different techniques in each application which in turns enhance the retrieval process. The paper aims to evaluate some of these applications and compare them to find out the proper methods that return the best results in these CBIR systems.

Highlights

  • The development in data storage and computing technologies made the demand for multimedia databases

  • Textual metadata is attached to each image in the database in order to use the same query retrieval techniques that are used in traditional databases which based on keywords

  • This paper aims to analyze the performance of some Content-Based Image Retrieval (CBIR) systems that uses different models and compare them to describe the effectiveness of certain factors in these systems and presenting the state of art for the existing query optimization techniques in multimedia databases

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Summary

Introduction

The development in data storage and computing technologies made the demand for multimedia databases. Textual metadata is attached to each image in the database in order to use the same query retrieval techniques that are used in traditional databases which based on keywords. This annotation process is a time-consuming task. All these factors decrease the performance of such systems that used this approach To overcome these shortcomings, the second approach which is Content-Based Image Retrieval (CBIR) has emerged. This paper aims to analyze the performance of some CBIR systems that uses different models and compare them to describe the effectiveness of certain factors in these systems and presenting the state of art for the existing query optimization techniques in multimedia databases.

Basic concepts
Multimedia databases
Query processing
Query optimization techniques
Semantic based retrieval
Metadata
Background
CBR for images
Applications
Digital libraries
Biodiversity information systems
Medical applications
Related work
Research problem
Analysis
Color descriptors
Shape descriptors
Texture descriptors
Experiment results
Conclusion
Future work and recommendations
Full Text
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