In　Traditional　Chinese　Medicine　(TCM),　tongue　diagnosis　is　an　indispensable　diagnostic　method.　Due　to　the　limitations　of　acquisition　devices　and　variations　of　the　illumination,　there　is　a　significant　color　distortion　between　the　captured　tongue　image　and　the　human　visual　perceived　image.　In　this　paper,　we　proposed　a　Two-phase　Deep　Color　Correction　Network　(TDCCN)　for　TCM　tongue　images.　In　the　first　phase,　a　deep　color　correction　network　was　designed　to　model　the　mapping　between　the　captured　image　and　the　target　objective　chromatic　values　under　a　standard　lighting　condition.　The　first　phase　provides　consistent　color　tongue　images　by　using　different　cameras　and　capture　devices.　The　output　tongue　images　at　this　phase　can　be　used　for　further　automatic　quantitative　analysis.　The　second　phase　provides　flexible　color　adjusting　options　to　adapt　to　different　work　environments　and　the　subjective　preference　of　doctors　for　visually　perceived　color　appearance.　Only　three　additional　parameters　are　used　to　describe　the　adjustment　operation.　Experimental　results　show　that　our　method　achieved　state-of-the-art　performance　in　objective　color　correction　and　obtained　satisfactory　perceptual　adaptation.