Images analysis by using fuzzy clustering

العناوين الأخرى

تحليل الصور باستخدام النقدة المضببة

المؤلف

Kharufah, Shahlah Hazim Ahmad

المصدر

al-Qadisiyah Journal for Computer Science and Mathematics

العدد

المجلد 11، العدد 1 (31 مارس/آذار 2019)، ص ص. 33-40، 8ص.

الناشر

جامعة القادسية كلية علوم الحاسوب و تكنولوجيا المعلومات

تاريخ النشر

2019-03-31

دولة النشر

العراق

عدد الصفحات

8

التخصصات الرئيسية

تكنولوجيا المعلومات وعلم الحاسوب

الملخص EN

The Fuzzy C-Mean algorithm is one of the most famous fuzzy clustering techniques.

The process of fuzzy clustering is a useful method in analyzing many patterns and images.

The Fuzzy C-Mean algorithm is widely used and based on the objective function reduction through adding membership values and the fuzzy coefficient.

The Mean Absolute Error (MAE) was also measured in this research for each execution.

The research found that when the number of clusters increases, the mean absolute error value is reduced.

When the number of clusters increased.

The more details in the resulting image were not present in the original image.

This helps in the analysis of the images.

In this research, medical images were treated and analyzed.

The analysis helps physicians explain the patient's health status and also according to suggested algorithm helps them to diagnose the possibility of a particular disease or tumor.

A Matlab program was created to perform the analysis.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Kharufah, Shahlah Hazim Ahmad. 2019. Images analysis by using fuzzy clustering. al-Qadisiyah Journal for Computer Science and Mathematics،Vol. 11, no. 1, pp.33-40.
https://search.emarefa.net/detail/BIM-971640

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Kharufah, Shahlah Hazim Ahmad. Images analysis by using fuzzy clustering. al-Qadisiyah Journal for Computer Science and Mathematics Vol. 11, no. 1 (2019), pp.33-40.
https://search.emarefa.net/detail/BIM-971640

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Kharufah, Shahlah Hazim Ahmad. Images analysis by using fuzzy clustering. al-Qadisiyah Journal for Computer Science and Mathematics. 2019. Vol. 11, no. 1, pp.33-40.
https://search.emarefa.net/detail/BIM-971640

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references : p. 39

رقم السجل

BIM-971640