Fatigue　driving　is　a　major　cause　of　traffic　accidents.　Real-time　driving　fatigue　detection　can　be　achieved　by　monitoring　the　variation　of　driver’s　driving　behavior,　such　as　nodding　phenomenon(it　can　be　detect　by　observing　head　position　changes)　can　be　applied　to　driver　drowsiness　detection.　In　the　traditional　algorithm　based　on　head　statement　detection,　however,　hardware　sensors　(such　as　HPS)　are　indispensible　to　feedback　head　position　information.　The　traditional　algorithms　using　hardware　sensors　are　difficult　to　gain　popularity　given　its　high　installation　and　maintenance　costs.　To　improve　this,　with　image　processing　technology,　lots　of　vision-based　algorithms　are　proposed　to　determine　head　position　for　driving　fatigue　detection.　However,　they　all　need　to　detect　face　organ　to　determine　the　head　status,　which　increase　the　calculation　cost　of　the　system.　In　this　paper,　face　organ　detection　is　replaced　by　hair　detection　and　head　status　recognition　is　achieved　based　on　the　variation　of　position　relation　between　face　and　hair　under　different　posture.　The　algorithm　presented　in　this　paper,　since　there　is　no　need　to　detect　face　organ,　can　be　applicable　to　low-resolution　images　and　blur　images.　©　2015,　Aracne　Editrice.　All　rights　reserved.