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• W1973438948 abstract "Human brain can detect faces from the images constructed in their eyes. The face detection is a computerize method of locating the face in the digital image. It is an important challenge to locate faces from uncontrolled and indistinguishable background of the digital image. This paper presents human face detection from the colored images. Skin color segmentation is used for localizations of skin colored components in the digital image. The features are extracted by using 2D-Discrete Cosine Transform (2D-DCT). The Back Propagation Neural Network (BPN) and Self Organization Map (SOM) are used for training and testing phases. In this research, total of 180 images have been used. About 60% of the images are used for training phase and 40% of the images are used for testing phase. The best detection rate has been obtained from BPN as 85.29% with the false positive rate of 6.18. However the best false positive rate is obtained from BPN as 5.05 with detection rate of 84.03%.These results are better than the results of existing methods of face detection using 2D-DCT" @default.
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• W1973438948 date "2009-01-01" @default.
• W1973438948 modified "2023-09-26" @default.
• W1973438948 title "Moving human detection and recognition in videos using adaptive method and support vector machine" @default.
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• W1973438948 doi "https://doi.org/10.1145/1838002.1838034" @default.
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