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 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Fuzzy C-means clustering algorithm with level set for MRI cerebral tissue segmentation
by: Maolood, Ismail Yaqub
Published: (2013) -
Detection of myocardial infarction in cardiac MRI colour-based K-means clustering segmentation /
by: Arifah Azura Abdul Latif
Published: (2010) -
Spatial Kernel-based Generalized C-mean Clustering for Medical Image Segmentation.
by: Lee, Song Yeow
Published: (2010) -
Image Segmentation With Cyclic Load Balanced Parallel
Fuzzy C - Means.
by: Vadiveloo, Mogana
Published: (2010) -
Optimized clustering with modified K-means algorithm
by: Alibuhtto, Mohamed Cassim
Published: (2021)