22-03-2016, 02:31 PM
watershed segmentation matlab code on retinal images
Image segmentation is the process of dividing an image into multiple parts. This is typically used to identify objects or other relevant information in digital images. There are many different ways to perform image segmentation, including:
Thresholding methods such as Otsu’s method
Thresholding methods such as Otsu’s method
Color-based Segmentation such as K-means clustering
Color-based Segmentation such as K-means clustering
Transform methods such as watershed segmentation
Transform methods such as watershed segmentation
Texture methods such as texture filters
Texture methods such as texture filters
An effective approach to performing image segmentation includes using algorithms, tools, and a comprehensive environment for data analysis, visualization, and algorithm development. See Image Processing Toolbox™ for more information.
Image segmentation is the process of dividing an image into multiple parts. This is typically used to identify objects or other relevant information in digital images. There are many different ways to perform image segmentation, including:
Thresholding methods such as Otsu’s method
Thresholding methods such as Otsu’s method
Color-based Segmentation such as K-means clustering
Color-based Segmentation such as K-means clustering
Transform methods such as watershed segmentation
Transform methods such as watershed segmentation
Texture methods such as texture filters
Texture methods such as texture filters
An effective approach to performing image segmentation includes using algorithms, tools, and a comprehensive environment for data analysis, visualization, and algorithm development. See Image Processing Toolbox™ for more information.
