Metode Fuzzy C-means merupakan algoritma pembelajaran tidak terawasi yang menggunakan derajat keanggotaan untuk menentukan cluster tiap-tiap titik data. Proses menjadi keunggulan dapat diterapkan pada gambar terdapat noise. Dilakukan modifikasi terhadap metode yaitu dengan melakukan penentuan dan perubahan matriks partisi fungsi fuzzy mendapatkan proses akurasi cluster. Penelitian ini bertujuan...

Nowadays, most fuzzy clustering algorithms are sensitive to the initialization results of and have a weak ability handle high-dimensional data. To solve these problems, we developed viewpoint-driven subspace c-means (VSFCM) algorithm. Firstly, propose new cut-off distance. Based on this, establish distance-induced (CDCI) method use it as strategy for cluster center viewpoint selection. Secondly...

Glioblastoma multiforme; Necrotic focus; Vasogenic edema; Bilateral filter; Contrast limited adaptive histogram equilization Abstract This paper does the qualitative comparison of Fuzzy C-means (FCM) and k-Means segmentation, with histogram guided initialization, on tumor edema complex MR images. The accuracy of any segmentation scheme depends on its ability to distinguish different tissue clas...

A biometric system provides automatic identification of an individual based on a unique feature or characteristic possessed by the individual. Among most of the biometric methods, Iris recognition is regarded as the most reliable and accurate biometric identification system. The performance of iris recognition system highly depends on the accurate segmentation. For the Iris Segmentation there i...