Content Based Image Retrieval System
CBIR: Content Based Image Retrieval
By
Rami Al-Tayeche (237262)
&
Ahmed Khalil (296918)
Supervisor: Professor Aysegul Cuhadar
A report submitted in partial fulfillment of the requirements of 94.498 Engineering Project
Department of Systems and Computer Engineering
Faculty of Engineering
Carleton University
April 4, 2003
Abstract
The purpose of this report is to describe our research and solution to the problem of designing a Content Based Image Retrieval, CBIR system. It outlines the problem, the proposed solution, the final solution and the accomplishments achieved. Due to the enormous increase in image database sizes, as well as its vast deployment in various applications, the need for CBIR development arose. Firstly, this report outlines a description of the primitive features of an image; texture, colour, and shape. These features are extracted and used as the basis for a similarity check between images. The algorithms used to calculate the similarity between extracted features, are then explained. Our final result was a MatLab built software application, with an image database, that utilized texture and colour features of the images in the database as the basis of comparison and retrieval. The structure of the final software application is illustrated. Furthermore, the results of its performance are illustrated by a detailed example.
Acknowledgements
We would like to thank our supervisor Professor Aysegul Cuhadar for her continuous feedback and support throughout the year that helped us throughout our project. We would also like to thank Professor Richard Dansereau, Assistant Professor at the Department of Systems and Computer Engineering, for his feedback. Furthermore, we acknowledge the support and feedback of our colleagues and friends, Osama Adassi, Nadia Khater, Aziz El-Solh, and Mike Beddaoui.
Table of Contents
1. Introduction to CBIR 1
1.1 Definition 1 1.2 Applications of CBIR 2 1.3 CBIR Systems 2
2.
By
Rami Al-Tayeche (237262)
&
Ahmed Khalil (296918)
Supervisor: Professor Aysegul Cuhadar
A report submitted in partial fulfillment of the requirements of 94.498 Engineering Project
Department of Systems and Computer Engineering
Faculty of Engineering
Carleton University
April 4, 2003
Abstract
The purpose of this report is to describe our research and solution to the problem of designing a Content Based Image Retrieval, CBIR system. It outlines the problem, the proposed solution, the final solution and the accomplishments achieved. Due to the enormous increase in image database sizes, as well as its vast deployment in various applications, the need for CBIR development arose. Firstly, this report outlines a description of the primitive features of an image; texture, colour, and shape. These features are extracted and used as the basis for a similarity check between images. The algorithms used to calculate the similarity between extracted features, are then explained. Our final result was a MatLab built software application, with an image database, that utilized texture and colour features of the images in the database as the basis of comparison and retrieval. The structure of the final software application is illustrated. Furthermore, the results of its performance are illustrated by a detailed example.
Acknowledgements
We would like to thank our supervisor Professor Aysegul Cuhadar for her continuous feedback and support throughout the year that helped us throughout our project. We would also like to thank Professor Richard Dansereau, Assistant Professor at the Department of Systems and Computer Engineering, for his feedback. Furthermore, we acknowledge the support and feedback of our colleagues and friends, Osama Adassi, Nadia Khater, Aziz El-Solh, and Mike Beddaoui.
Table of Contents
1. Introduction to CBIR 1
1.1 Definition 1 1.2 Applications of CBIR 2 1.3 CBIR Systems 2
2.
References: 6. Linda G. Shapiro, and George C. Stockman, Computer Vision, Prentice Hall, 2001. 8. R. Jain, R. Kasturi, and B. G. Schunck, Machine Vision, McGraw Hill International Editions, 1995. 17. Marinette Bouet, Ali Khenchaf, and Henri Briand, “Shape Representation for Image Retrieval”, 1999, [Online Document], Available at: http://www.kom.e-technik.tu-darmstadt.de/acmmm99/ep/marinette/