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A New Image Segmentation Method Based on Grey Graph Cut
By: Jiao He; Miao Ma; Hongpeng Tian; Hualei Guo;
2010 / IEEE / 978-1-4244-6813-3
Description
This item was taken from the IEEE Conference ' A New Image Segmentation Method Based on Grey Graph Cut ' To improve the performance of image segmentation, the paper suggests a new image segmentation method based on grey graph cut, which integrates grey theory and graph cut theory. In the method, the image is taken as a weighted undirected graph first. And then, after the relationships of grey-levels and positions in local regions are discussed via grey relational analysis, a grey weight matrix is established, based on which a grey partition function is constructed. Next, the image is binarized with the gray-level that corresponds to the minimum value of the grey partition function. Experimental results on visible light image and SAR image indicate that the proposed method, being superior to some existing methods like Otsu and Normalized Cut etc., not only can segment the images with obvious difference between targets and backgrounds, but also suppress image noise effectively.
Related Topics
Sar Image
Image Segmentation Method
Grey Graph Cut
Grey Relational Analysis
Grey Partition Function
Image Segmentation
Graph Theory
Pixel
Computer Science
Image Analysis
Optimization Methods
Helium
Signal To Noise Ratio
Data Structures
Image Processing
Grey Theory
Image Segmentation
Graph Cut
Normalized Partition
Image Segmentation
Image Denoising
Graph Theory
Matrix Algebra
Engineering
Visible Light Image