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A shape context based Hausdorff similarity measure in image matching 会议论文
INTERNATIONAL SYMPOSIUM ON PHOTOELECTRONIC DETECTION AND IMAGING 2013: INFRARED IMAGING AND APPLICATIONS, Beijing, June 25-27, 2013
Authors:  Ma TL(马天磊);  Liu YP(刘云鹏);  Shi ZL(史泽林);  Yin J(尹健)
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The Traditional Hausdorff Measure  Which Uses Euclidean Distance Metric (L2 Norm) To Define The Distance Between Coordinates Of Any Two Points  Has Poor Performance In The Presence Of The Rotation And Scale Change Although It Is Robust To The noIse And Occlusion. To Address The Problem  We DefIne a Novel Similarity Function IncludIng Two Parts In ThIs Paper. The First Part Is Hausdorff dIstance betWeen Shapes Which Is Calculated By exploitIng Shape Context That Is Rotation And Scale Invariant As The dIstance Metric. The Second Part Is The Cost Of matchIng betWeen Centroids. Unlike The Traditional Method  We Use The Centroid As Reference Point To Obtain Its Shape COntext That Embodies Global InformatiOn Of The Shape. Experiment Results DemOnstrate That The FunctiOn Value betWeen Shapes Is RotatiOn And Scale Invariant And The Matching Accuracy Of Our Algorithm Is Higher Than That Of Previously Proposed Algorithm On The Mepg-7 databAse.