Considering　the　fact　that　pornographic　images　are　flooding　on　the　web,　we　propose　a　pornographic　image　recognition　method　based　on　convolutional　neural　network.　This　method　can　be　divided　into　two　parts:　coarse　detection　and　fine　detection.　Because　majority　of　images　are　normal,　we　use　coarse　detecting　to　quickly　identify　the　normal　images　with　no　or　fewer　skin-color　regions　and　facial　images.　For　the　images　which　contain　much　more　skin-color　regions,　they　need　further　identification　through　fine　detecting.　At　first,　we　trained　the　CNN　using　the　strategy　of　pre-training　mid-level　features　non-fixed　fine-tuning,　then　based　on　the　trained　model,　we　can　classify　whether　the　image　is　pornographic　or　not.　Compared　with　exiting　methods,　performance　of　our　method　is　better　than　the　state-of-the-art.