Research on Crack Segmentation and Identification Method for Downhole TV Images Based on Differential Box Dimension Algorithm
The key to interpreting lithology and fractures is to identify,segment,and extract crack width from downhole TV images of rock core integrity.At present,the imaging re-sults of downhole television are mainly identified and interpreted through manual methods,which requires a large workload and is easily influenced by subjective factors.This paper fo-cuses on the segmentation and recognition of downhole television images.Starting from frac-tal theory,this paper proposes to extract the lithological changes by the differential box counting(DBC)algorithm and rock texture features such as cracks and fissures from down-hole television images.Then,the K-means clustering algorithm based on the optimal num-ber of clusters is used to perform texture segmentation on downhole television images,achie-ving automatic rock layer partitioning of downhole television images.The results show that by combining the Canny edge detection algorithm to extract crack width information,the ac-curacy of crack recognition reaches 94.2％,achieving accurate layering of lithology and fine identification of cracks.Compared with the 2D Log-Gabor algorithm,the differential box di-mension algorithm has better segmentation performance and faster speed for downhole TV images.
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