Using genetic algorithm in clustering image

Dissertant

al-Sadi, Muna Yusuf al-Saghir

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

• Data processing
• Digital electronics

• APA
• MLA
• AMA

Language

English

Data Type

Arab Theses

Record ID

BIM-305275