In　this　paper　we　present　a　novel　method　called　color　support　Normal　Iterative　Closest　Point　(color　NICP)　to　recursively　align　point　clouds.　First　of　all,　the　matching　criterion　of　NICP　is　improved　based　on　the　uncertainty　analysis　on　the　feature　points　and　L*a*b*　color　space.　Secondly,　a　six-dimensional　k-d　tree　based　nearest　neighbor　search　is　used　to　match　corresponding　points　between　the　clouds.　Our　algorithm　takes　advantage　of　not　only　the　3D　structure,　but　also　the　texture　information　of　color　image.　Extensive　experiments　show　that　our　color　NICP　algorithm　improves　the　robustness　and　precision　of　point　cloud　registration.