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- W2328492397 abstract "One of the major characteristics of human face is shown in the spatial curvature properties of face surface. The spatial curvature in object images can be represented by a set of gradient directions of the sub surfaces of the images. The image is appropriately divided into the same size of patches. Each patch is the sub surface of the image. A facet function on a patch can be obtained using the gray values of the pixels in the patch. A set of gradient directions of a group of the facet functions reflects one of the inherent curvatures of a face image. Two coefficients of the facet function indicate the gradient at the center of the patch. These coefficients form feature vectors for face discrimination or recognition. Computer computation suggests that the patch size of 5x5 yields the most precise recognition rate of 96.5." @default.
- W2328492397 created "2016-06-24" @default.
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- W2328492397 date "2005-12-12" @default.
- W2328492397 modified "2023-09-23" @default.
- W2328492397 title "Upgrading the precision of face recognition using the gradient of a facet function" @default.
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- W2328492397 doi "https://doi.org/10.1117/12.664486" @default.
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