Content-based indexing methods are of great interest for image and video retrieval in audio-visual archives, such as in the DiVAN project that we are currently developing. Detecting and recognizing human faces automatically in video data provide users with powerful tools for performing queries. The work is done for recognition of the face by using wavelet packet decomposition.
Each face is described by a subset of band filtered images containing wavelet coefficients. These coefficients characterize the face texture and a set of simple statistical measures allow us to form compact and meaningful feature vectors. An efficient and reliable probalistic metric derived from the Bhattacharyya distance is used in order to classify the face feature vectors into person classes.
By Dr. Aziz Makandar | Mrs. Rashmi Somshekhar | Ms. Smitha M" Face Recognition by using wavelet based frame work"
Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-5 , August 2018,
Paper URL: http://www.ijtsrd.com/papers/ijtsrd17067.pdf
Direct URL: http://www.ijtsrd.com/computer-science/artificial-intelligence/17067/face-recognition-by-using-wavelet-based-frame-work/dr-aziz-makandar
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