Images Analysis by Using Fuzzy Clustering | ||
| Journal of Al-Qadisiyah for Computer Science and Mathematics | ||
| Article 1, Volume 11, Issue 1, April 2019, Pages 33-40 PDF (0 K) | ||
| Author | ||
| Shahla Hazim Ahmed Kharofa | ||
| Abstract | ||
| 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. | ||
| Keywords | ||
| Fuzzy Clustering; Fuzzy C; Mean Algorithm; Matlab Language; Image analysis; Mean Absolute Error | ||
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