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Face Recognition: Using the Neural Spatial-Temporal Segmentation to Extract the Face Feature and Performing the Feature Geometry Comparison
Taipei, Taiwan November 11-November 13
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MMSE.2000.8972292000 International Symposium on Multi ...
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This research uses - the boundary cutting, spatial-temporal segmentation, block based searching, and gray scale histogram technique to extract the eyes, nose, and mouth images. In this research, the gray scale histogram are used to salient the eyes, nose, and mouth features. A spatial-temporal template is designed to slide the eyes, nose, and mouth images to extract the eyes, nose, and mouth image. In order to obtain the better result, the generic algorithm and spatial region partition technique need to be invested to remove the noise and to precisely bind the object region to obtain the more accurate extracting result.
Index Terms:
Object extraction, boundary cutting, spatial-temporal segmentation, block-based searching, and gray scale histogram.
Citation:
Ching-Liang Su, "Face Recognition: Using the Neural Spatial-Temporal Segmentation to Extract the Face Feature and Performing the Feature Geometry Comparison," mse, pp.321, 2000 International Symposium on Multimedia Software Engineering, 2000
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