In　this　paper　a　Kernel　Partial　Least　Squares　Regression　(K-PLSR)-based　color　correction　method　for　Traditional　Chinese　Medicine　(TCM)　tongue　images　under　different　illumination　conditions　has　been　proposed.　The　captured　values　under　different　illumination　conditions　and　their　reference　values　of　24　patches　in　the　Munsell　colorchecker　are　respectively　considered　as　the　input　and　the　output.　The　mapping　model　between　the　input　and　the　output　is　established　by　using　the　K-PLSR　method　in　the　device-independent　CIE　LAB　color　space.　The　mapping　model　is　then　applied　to　correct　the　captured　tongue　images.　Experimental　results　show　that,　using　the　proposed　method,　the　average　color　difference　of　each　color　patch　is　only　0.821　after　correction.　For　the　subjective　results,　tongue　images　under　different　illumination　conditions　can　obtain　consistent　correction　results,　which　is　beneficial　for　subsequent　standardized　tongue　image　storage　and　automatic　analysis　in　tongue　diagnosis　of　TCM.　Compared　with　the　most　commonly　used　polynomial-based　correction　method　and　support　vector　regression　based　correction　method,　whether　for　the　subjective　or　objective　evaluation,　the　proposed　method　can　obtain　a　superior　color　correction　performance.　(C)　2015　Elsevier　B.V.　All　rights　reserved.