Using genetic algorithm in clustering image

مقدم أطروحة جامعية

al-Sadi, Muna Yusuf al-Saghir

الجامعة

الجامعة التكنولوجية

الكلية

-

القسم الأكاديمي

قسم علوم الحاسوب

دولة الجامعة

العراق

الدرجة العلمية

ماجستير

تاريخ الدرجة العلمية

2009

الملخص الإنجليزي

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.

التخصصات الرئيسية

تكنولوجيا المعلومات وعلم الحاسوب

الموضوعات

• معالجة البيانات
• الإلكترونيات الرقمية

• APA
• MLA
• AMA

لغة النص

الإنجليزية

نوع البيانات

رسائل جامعية

رقم السجل

BIM-305275