Vehicle　detection　is　a　major　way　of　subtracting　moving　vehicles　from　traffic　flow　images　in　ITS.　In　order　to　acquire　an　accurate　background　from　the　constantly　changing　traffic　environment,　we　design　and　realize　a　robust　background　updating　model　based　on　single　Gaussian　distribution.　Then,　we　use　the　method　of　local　normalization　to　subtract　the　texture　image,　and　carry　out　texture　segmentation　to　acquire　the　moving　vehicles　by　virtue　of　the　Laws＇　texture　energy　method.　The　experiment　shows　that　this　method　can　efficiently　eliminate　the　effect　of　the　vehicle　shadows　and　bright　pavements　and　it　is　especially　suitable　for　the　nighttime　vehicle　detection　in　complex　traffic　environments　with　streetlights.　©2010　IEEE.