Using genetic algorithm in clustering image
Dissertant
University
University of Technology
Faculty
-
Department
Computer Sciences Department
University Country
Iraq
Degree
Master
Degree Date
2009
English Abstract
The clustering problem has been addressed in many contexts and by researchers in many disciplines ; this reflects its broad appeal and usefulness as one of the steps in exploratory data analysis.
With cluster analysis it is possible tp determine a wide variety of procedures that can be used to- create groups of cases, which are more similar than all the others.
In this thesis, an optimization approaches based on clustering technique is introduced for finding optimal image segmentation.
The design and implementation of proposed system are described, where the proposed system are based on the concept of clustering where consists of two main techniques (Thresholding and Genetic Algorithm(GA)) with three proposed features (gray value, distance, gray connection).
The different proposed implementation segmentation techniques of the proposed system were tested using Gray Scale Image and different size.
Results reported show good performance.
Comparisons between two strategies are also given.
System performance shows that GA is promising for solving image segmentation problem.
All programs in thise algorithms arc built by using Visual Basic Language.
Main Subjects
Information Technology and Computer Science
Topics
American Psychological Association (APA)
al-Sadi, Muna Yusuf al-Saghir. (2009). Using genetic algorithm in clustering image. (Master's theses Theses and Dissertations Master). University of Technology, Iraq
https://search.emarefa.net/detail/BIM-305275
Modern Language Association (MLA)
al-Sadi, Muna Yusuf al-Saghir. Using genetic algorithm in clustering image. (Master's theses Theses and Dissertations Master). University of Technology. (2009).
https://search.emarefa.net/detail/BIM-305275
American Medical Association (AMA)
al-Sadi, Muna Yusuf al-Saghir. (2009). Using genetic algorithm in clustering image. (Master's theses Theses and Dissertations Master). University of Technology, Iraq
https://search.emarefa.net/detail/BIM-305275
Language
English
Data Type
Arab Theses
Record ID
BIM-305275