Object　modeling　by　the　registration　of　multiple　range　images　has　important　applications　in　reverse　engineering　and　computer　vision.　In　order　to　register　multi-view　scattered　point　clouds,　a　novel　curvature-based　automatic　registration　algorithm　is　proposed　in　this　paper,　which　can　solve　the　registration　problem　with　partial　overlapping　point　clouds.　For　two　sets　of　scattered　point　clouds,　the　curvature　of　each　point　is　estimated　by　using　the　quadratic　surface　fitting　method.　The　feature　points　that　have　the　maximum　local　curvature　variations　are　then　extracted.　The　initial　matching　points　are　acquired　by　computing　the　Hausdorff　distance　of　curvature,　and　then　the　circumference　shape　feature　of　the　local　surface　is　used　to　obtain　the　accurate　matching　points　from　the　initial　matching　points.　Finally,　the　rotation　and　translation　matrix　are　estimated　by　the　quaternion,　and　an　iterative　algorithm　is　used　to　improve　the　registration　accuracy.　Experimental　results　show　that　the　algorithm　is　effective.©　2012　Elsevier　Ltd.　All　rights　reserved.