Abstract -Thb paper proposes a parallel Fauy C-Mean (FCM) algorithm for image segmentation. The sequential FCM algorithm is computationally intensive and has significant memory requirements. For many applications such as medical image segmentation and geographical image analysis that deal with large size images, sequenrial FCM is very slow. In our parallel FCM algorithm, dividing the compatations among the processors and minimizing the need for accessing secondary storage, enhance the performance and efficiency of image segmentation task as compared to the sequential algorithm
In REF , the authors proposed a parallel FCM implementation on a parallel architecture, based on dividing the computation among the processors for image segmentation analysis.
A parallel Fuzzy C-Mean algorithm for image segmentation
IEEE Annual Meeting of the Fuzzy Information, 2004. Processing NAFIPS '04.
IEEE Annual Meeting of the Fuzzy Information, 2004. Processing NAFIPS '04.
Computer Science