Interactive graph cut method based on improved Gabor features for image segmentation

2011 ◽  
Author(s):  
Dongliang Yang ◽  
Tingquan Deng ◽  
Chengdong Yang ◽  
Jilong Bian
Keyword(s):  
Image Segmentation ◽  
Graph Cut ◽  
Gabor Features ◽  
Cut Method

scholarly journals Optimized Graph cut Color Image Segmentation using Genetic Algorithm with Weighted Constraints (OGcut)

2019 ◽  
Vol 8 (4S2) ◽  
pp. 583-587
Keyword(s):  
Genetic Algorithm ◽  
Image Segmentation ◽  
Color Image ◽  
Graph Cut ◽  
Input Image ◽  
Color Image Segmentation ◽  
Weighted Constraints ◽  
Mutation Operators ◽  
Cut Method ◽  
Crossover And Mutation

This paper proposes a Novel color image segmentation using Graph cut method by minimizing the weighted energy function. This method is applying a pair of optimal constraints namely: color constraint and gradient constraint. In the state-of-the-art methods, the background and foreground details are manually initialized and used for verifying the smoothness of the region. But in this proposed method, they are dynamically calculated from the input image. This feature of the proposed method can be used in color image segmentation where more number of unique segments exists in a single image. The genetic algorithm is applied to the graph obtained from the graph cut method. The crossover and mutation operators are applied on various subgraphs to populate the different segments.

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