Color Image Segmentation Method Based on Region Growing and Ant Colony Clustering

Author(s):  
Xinyan Mao ◽  
Binjie Sun ◽  
Ying Zhang ◽  
Yanxiao Hu
2021 ◽  
Vol 58 (2) ◽  
pp. 0210023
Author(s):  
李新颖 Li Xinying ◽  
冉思园 Ran Siyuan ◽  
廉敬 Lian Jing

A new heuristic algorithm for porosity segmentation for the colored petro-graphic images is proposed. The proposed algorithm automatically detects the porosities that represent the presence of oil, gas, or even water in the analyzed thin section rock segment based on the colour of the porosity area filled with dies in the analyzed sample. For the purpose of the oil exploration, the thin section fragments are died in order to emphasize the porosities that are analyzed under the microscope. The percentage of the porosity is directly proportional to the probability of the oil, gas, or even water presence in the area where the drilling is performed (i.e. the increased porosity indicates the higher probability of oil existence in the region). The proposed automatic algorithm shows better results than the existing K-means segmentation method.


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