A　specific　face　recognition　system　designed　on　ARM9　architecture　embedded　platform　is　proposed　in　this　paper.　By　using　the　method　of　skin　model　combined　with　Haar-like　features　to　detect　faces　and　PCA　(principal　component　analysis)　dimension　declining　algorithm　to　recognize　the　face.　Firstly,　the　libraries　of　QT　and　OpenCV　are　transplanted　into　the　ARM9　platform　which　constructs　the　basis　of　all　the　programs　in　the　system.　In　addition,　the　training　sample　data　are　made　and　then　transmitted　to　the　embedded　system.　After　that　the　processed　face　images　are　recognized　by　using　the　nearest　distance　algorithm.　Experiments　show　that　this　design　on　the　platform　of　ARM　9　embedded　system　has　boosted　the　efficiency　of　embedded　face　recognition　system,　especially　in　the　case　of　needing　huge　data　processing.