Comparison of fuzzy C means and K means clustering technique using color segmentation for prostate cancer cell images / Nuratiqah Mohd Zahari
Segmentation of an image entails the division or separation of the image into regions of similar attribute. The most basic attribute for segmentation of an image is its color components for a color image. Clustering is one of the methods used for segmentation. The aim of the project is to investigat...
Saved in:
Main Author: | Mohd Zahari, Nuratiqah |
---|---|
Format: | Thesis |
Language: | English |
Published: |
2012
|
Online Access: | https://ir.uitm.edu.my/id/eprint/87116/1/87116.pdf https://ir.uitm.edu.my/id/eprint/87116/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Comparative Study Of Fuzzy C-Means And K-Means Clustering Techniques
by: Sharifah Sakinah, Syed Ahmad
Published: (2014) -
Modeling of vehicle trajectory using K-means and fuzzy C-means clustering
by: Choong, Mei Yeen, et al.
Published: (2019) -
MRI brain lesion image detection based on color-converted K-means clustering segmentation
by: Li, Hong Juang, et al.
Published: (2010) -
An Intelligent System A Comparative Study Of Fuzzy C-Means And K-Means Clustering Techniques
by: Afirah, Taufik
Published: (2013) -
Segmentation of acne lesions using K-means clustering
by: Ramli, Roshaslinie, et al.
Published: (2011)