A　novel　skin　detection　method　in　JPEG　compressed　domain　has　been　proposed　in　this　paper.　Color　and　texture　features　of　the　image　blocks　are　extracted　from　the　entropy　decoded　DCT　coefficients　firstly.　Then,　data　mining　method,　i.e.　decision　tree,　is　applied　to　establish　the　skin　color　model　to　describe　the　relationship　between　the　features　of　image　blocks　and　the　skin　detection　results,　afterwards,　the　initial　skin　regions　are　detected　based　on　the　skin　color　model.　The　skin　regions　are　finally,　segmented　through　region　growing　method.　Experimental　results　show　that,　compared　with　the　SPM　(Skin　Probability　Map)　skin　detection　method　in　the　pixel　domain,　the　proposed　method　can　achieve　higher　detection　accuracy　as　well　as　higher　speed.　©　2009　IEEE.