Research on threshold segmentation algorithm of coal CT images based on improved Otsu

The accuracy of CT image threshold selection is very important for the 3D reconstruction model to restore the real coal structure. Excessive segmentation of pores and fractures in coal CT images by Otsu results in the model structure not conforming to the reality. To overcome this defect, we first explored the failure mechanism of Otsu method on coal CT images, and then a modified method, called MP-Otsu, was present. Finally, Matlab software was used to detect the 2D segmentation effect of MP-Otsu method on CT images. Meanwhile, Avizo software was used to carry out 3D reconstruction of coal pores and fractures and compared the changes of pores and fractures parameters before and after improvement. Results showed that the minerals in coal and the threshold determined by Otsu showed significant positive correlation. The variance of target and background was very different due to the existence of internal mineral components. What’s more, low porosity contributed to the unimodal distribution of CT images’ grayscale distribution histogram and cannot provide enough variance information. All these features of coal were reasons that Otsu failed to segment the CT images. The MP-Otsu method introduced three weight factors such as the fitting curve slope of mineral content and Otsu threshold and approximate proportion of the target in the image, to improve the Otsu threshold segmentation method. The binarization images obtained were highly consistent with the original images and could accurately segment the target area of pores and fractures. Compared with Otsu method, the porosity and maximum throat size of 3D reconstruction model were reduced by 96.18% and 80.07% respectively, which effectively overcame the defect of Otsu’s over segmentation of coal CT images. This study may contribute to further exploring the physical characteristics of coal related to pores and fractures