*Article* **The Classification of Inertinite Macerals in Coal Based on the Multifractal Spectrum Method**

**Man Liu 1, Peizhen Wang 1,2,\*, Simin Chen <sup>1</sup> and Dailin Zhang <sup>3</sup>**


Received: 12 November 2019 ; Accepted: 8 December 2019; Published: 14 December 2019

**Abstract:** Considering the heterogeneous nature and non-stationary property of inertinite components, we propose a texture description method with a set of multifractal descriptors to identify different macerals with few but effective features. This method is based on the multifractal spectrum calculated from the method of multifractal detrended fluctuation analysis (MF-DFA). Additionally, microscopic images of inertinite macerals were analyzed, which were verified to possess the property of multifractal. Simultaneously, we made an attempt to assess the influences of noise and blur on multifractal descriptors; the multifractal analysis was proven to be robust and immune to image quality. Finally, a classification model with a support vector machine (SVM) was built to distinguish different inertinite macerals from microscopic images of coal. The performance evaluation proves that the proposed descriptors based on multifractal spectrum can be successfully applied in the classification of inertinite macerals. The average classification precision can reach 95.33%, higher than that of description method with gray level co-occurrence matrix (GLCM; about 7.99%).

**Keywords:** coal; inertinite macerals; classification; multifractal analysis; support vector machine
