Edge detection based on ANFIS
2016-08-23
0 0 0
3.3
Other
Earn points
One of the most important topics in image processing is edge detection.
Many methods have been proposed for this end but most of them have weak performance in noisy images because noise pixels are determined as edge.
In this Project, two new methods are represented based on Hierarchical Adaptive Neuro Fuzzy Systems (HANFIS).
Each method consists of desired number of HANFIS operators that receive the value of some neighbouring pixels and decide
central pixel is edge or not. Simple train images are used in order to set internal parameters of each HANFIS operator.
The experimental results show that these methods are robust against impulse noise and extract edge pixels exactly.
Many methods have been proposed for this end but most of them have weak performance in noisy images because noise pixels are determined as edge.
In this Project, two new methods are represented based on Hierarchical Adaptive Neuro Fuzzy Systems (HANFIS).
Each method consists of desired number of HANFIS operators that receive the value of some neighbouring pixels and decide
central pixel is edge or not. Simple train images are used in order to set internal parameters of each HANFIS operator.
The experimental results show that these methods are robust against impulse noise and extract edge pixels exactly.
matlab
检测
anfis
基于
边缘
Related Source Codes
GMSK Linear Receiver
0
0
no vote
NSGA-II algorithm
0
0
no vote
NSGA-III multi-objective optimization algorithm
0
0
no vote
Compressed sensing example
0
0
no vote
CFAR detector example
0
0
no vote
No comment