The precise determination of mineral chemical composition is significance to the exploitation and utilization of mineral resources, and inversion of SiO2 content in iron ore by thermal infrared spectrum makes up for the shortcomings of the traditional methods in terms of time-consuming and so on. The thermal infrared spectrum of iron ore, however, is affected by surface roughness and other factors, which results in the decrease of the inversion accuracy of SiO2 content. The recent study doesn’t consider the influence of ore surface roughness on the inversion of ore composition and quantitatively inverted SiO2 content in iron ore by thermal infrared spectrum. The inversion result can’t provide any effective help for precise delineation of ore body range and ore blending. Therefore, this paper aims roughness on the factor to influence the inversion of SiO2 content in iron ore. Taking the “Anshan-type” iron ore in Liaoning Province as the research object, the samples are made into a total of 14 blocks of cylindrical blocks with a diameter of 6 cm and a thickness of 1 cm, which formed a sequence according to their SiO2 content. Two levels of roughnesses are made on both sides of each sample, and the surface roughness is observed by using Surtronic S128 roughness meter. The infrared spectroradiometer Turbo FT is used to observe the thermal infrared spectroscopy emissivities of samples. The correlation indexes between the spectral index and SiO2 content are analyzed by the normalized index (NDI) to determine the sensitive bands of SiO2 content of two grade roughness samples. Located at 8.12~8.13, 8.02~8.03 μm, the correlation coefficients are 0.947 and 0.972, respectively. A quantitative inversion model of the sensitive band and SiO2 content is established to analyze the effect of roughness on the inversion of SiO2 content. The results show that: (1) The increase of roughness Rq has a significant effect on the spectral emissivity of RF(Reststrahlen Features) characteristic regions. The average roughness Rq is increased from 1.05 to 2.47 μm, so that the maximum difference between the rough surface and the smooth surface emissivity of the same sample is 0.17 (relative difference 42.9%). (2) When the same grade roughnesses are used for content inversion, the inversion error is small, and the average absolute error is 1.88%. The inversion accuracy of most samples can meet the error requirements of the geological and mineral industry standards. (3) The experimental results of inversion SiO2 content accuracy are great higher than the inversion accuracy of 3.57% without considerating the iron ore surface morphology, and the relative improvement accuracy is 47.3%. Therefore, considering the influence of roughness is of great significance for improving the inversion accuracy of SiO2 content, then it is of great significance to realize the precise division of iron ore and mine iron ore resources reasonably and efficiently.