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http://dx.doi.org/10.9708/jksci.2010.15.11.067

An Improved Face Detection Method Using a Hybrid of Hausdorff and LBP Distance  

Park, Seong-Chun (단국대학교 컴퓨터 학부)
Koo, Ja-Young (단국대학교 컴퓨터 학부)
Publication Information
Journal of the Korea Society of Computer and Information / v.15, no.11, 2010 , pp. 67-73 More about this Journal
Abstract
In this paper, a new face detection method that is more accurate than the conventional methods is proposed. This method utilizes a hybrid of Hausdorff distance based on the geometric similarity between the two sets of points and the LBP distance based on the distribution of local micro texture of an image. The parameters for normalization and the optimal blending factor of the two different metrics were calculated from training sample images. Popularly used face database was used to show that the proposed method is more effective and robust to the variation of the pose, illumination, and back ground than the methods based on the Hausdorff distance or LBP distance. In the particular case, the average error distance between the detected and the true face location was reduced to 47.9% of the result of LBP method, and 22.8% of the result of Hausdorff method.
Keywords
Face detection; Local Binary Pattern, LBP; Hausdorff Distance;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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