To address the issue of insufficient detection accuracy for hollow disease boundaries in existing rock paintings, this study utilizes thermal infrared imaging to acquire two-dimensional temperature field data. By reconstructing the heat flux density field through Fourier's law, we discover that the temperature distribution along hollow characteristic lines exhibits significant Gaussian distribution characteristics. Accordingly, a Gaussian function model is constructed to characterize the temperature field distribution. Through parameter sensitivity analysis, we propose a width criterion based on thermal accumulation ratio as the core parameter, and establish a quantitative identification standard for hollow boundaries. To verify the effectiveness of proposed method, 50 sets of comparative experiments are conducted using hardness testing and proposed methods in the Damaidi rock paintings. Experimental results demonstrate that the discrete sampling hardness method, limited by probe size and scale graduations, exhibits boundary interpolation errors up to ±1.5 cm and fails to achieve continuous boundary characterization. In contrast, the proposed method enhances the spatial resolution of hollow boundaries through Gaussian model analysis of temperature distribution along characteristic lines, enabling continuous damage characterization.