Taken　the　requirements　of　web　pornographic　image　recognition　both　on　precision　and　speed,　a　pornographic　image　recognition　method　based　on　Oriented　FAST　and　Rotated　BRIEF　(ORB)　is　proposed　in　this　paper.　The　whole　recognition　process　can　be　divided　into　two　parts:　coarse　detection　and　fine　detection.　Coarse　detection　can　identify　the　non-pornographic　images　with　no　or　fewer　skin-color　regions　and　facial　images　quickly.　For　the　remaining　images　containing　much　more　skin-color　regions,　fine　detection　is　conducted,　which　includes　three　steps:　(1)　extract　ORB　descriptors　from　the　skin-color　regions　and　represent　the　descriptors　based　on　Bag　of　Words　(BOW)　model,　(2)　construct　the　feature　vector　combining　ORB　feature　with　72-dimensional　Hue,　Saturation,　Value　(HSV)　color　feature　of　the　whole　image,　(3)　train　the　classification　model　using　Support　Vector　Machine　(SVM)　and　apply　it　for　image　recognition.　The　experimental　results　show　that　the　proposed　method　can　obtain　better　recognition　precision　and　drastically　reduce　the　average　time　cost　to　1/4　of　the　method　based　on　Scale　Invariant　Feature　Transform　(SIFT).　(C)　2015　Elsevier　B.V.　All　rights　reserved.