Color Image Segmentation Using Fuzzy C-Regression Model
Image segmentation is one important process in image analysis and computer vision and is a valuable tool that can be applied in fields of image processing, health care, remote sensing, and traffic image detection. Given the lack of prior knowledge of the ground truth, unsupervised learning technique...
Saved in:
Main Authors: | Min Chen, Simone A. Ludwig |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2017-01-01
|
Series: | Advances in Fuzzy Systems |
Online Access: | http://dx.doi.org/10.1155/2017/4582948 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Color Image Segmentation Based on Different Color Space Models Using Automatic GrabCut
by: Dina Khattab, et al.
Published: (2014-01-01) -
Infrared image segmentation algorithm based on distribution information intuitionistic fuzzy c-means clustering
by: Xiaofei WANG, et al.
Published: (2020-05-01) -
Adaptive Semi-Supervised Fuzzy C-Means Method With Local Spatial Information and Pre-Clustering for Image Segmentation
by: Hao-Ran Chen, et al.
Published: (2024-01-01) -
Molecular Image Segmentation Based on Improved Fuzzy Clustering
by: Jinhua Yu, et al.
Published: (2007-01-01) -
Visual Sensor Based Image Segmentation by Fuzzy Classification and Subregion Merge
by: Huidong He, et al.
Published: (2017-01-01)