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.　©　2025　Universitat　zu　Koln.　All　rights　reserved.