• The Journal of Engineering Research
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• v.1 no.1
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• pp.65-70
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• 1997

To transmit the degraded voice signal within various environment surrounding acoustic noises, we extract lip i the face and then compare lip edge features with prestoring DB having features such as mouth height, width, area, and rate. It provides high security and is not affected by acoustic noise because it is not necessary to transmit the actual utterance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.12
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• pp.2547-2554
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• 2009

In this paper, we proposed a face detection algorithm and a hardware implementation method for ROI(Region Of Interest) of AF(Auto Focusing). We used face features in skin regions of YCbCr color space for face detection. The face features are the number of skin pixels in face regions, edge pixels in eye regions, and shadow pixels in lip regions. The each feature was statistically selected by 2,000 sample pictures of face. The proposed algorithm detects two faces that are closer center of the image for considering the effectiveness of hardware resource. The detected faces are displayed by rectangle for ROI of AF, and the rectangles are represented by positions in the image about starting point and ending point of the rectangles. The proposed face detection method was verified by using FPGA boards and mobile phone camera sensor.