An Improved Object Detection Method using Hausdorff Distance Modified by Local Pattern Similarity

Kyoungsik Cho; KOO JA YOUNG

Journal of The Korea Society of Computer and Information

Abbr : JKSCI
2007, 12(6), pp.147-152
Publisher : The Korean Society Of Computer And Information
Research Area : Computer Science

Kyoungsik Cho ¹ , KOO JA YOUNG ²

¹ 강원관광대학
² 단국대학교

ABSTRACT

Face detection is a crucial part of the face recognition system. It determines the performance of the whole recognition system. Hausdorff distance metric has been used in face detection and recognition with good results. It defines the distance metric based only on the geometric similarity between two sets of points. However, not only the geometry but also the local patterns around the points are available in most cases. In this paper a new Hausdorff distance measure is proposed that makes hybrid use of the similarity of the geometry and the local patterns around the points. Several experiments shows that the new method outperforms the conventional method.
KEYWORDS

Hausdorff distance , Pattern Matching , Face detection
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KCI Citation (2)

KJC Korea
Journal Central

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