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Viewing 1-4 of 4 total results
 wjert, 2018, Vol. 4, Issue 4, 160-167. Original Article ...
alogrithm for one-sample face recognition using HMM Model of fiducial areas. It used 2D Discrete Wavelet Transform to extract features from images and Hidden Markov Model was used for training, recognition and classification. 90% recognition accuracy was recorded when tested on a subset of AT&T face database. Adedeji et.
Automatic local Gabor features extraction for face recognition
Automatic local Gabor features extraction for face recognition Yousra BEN JEMAA ... Face recognition is a very challenging area in computer vision ... include hidden Markov model (HMM) [19], elastic bunch graph matching algorithm [3] and local feature analysis.
FACE PROFILE RECOGNITION AND IDENTIFICATION
proposed for automatic person identification using face profile images. The commonly used methods for face profile recognition include: Scale space filtering [1], Morphological transform [2, 3], Dynamic time warping [4], Attributed string [5], and Hidden Markov model [6, 7].
Advanced Signal Processing and Pattern Recognition Methods ...
The next paper, by P. R. Nicholl et al., performs face recognition by combining the multiresolution feature of the discrete wavelet transform (DWT) with the local interactions of the facial structures expressed through the structural hidden Markov model (SHMM). Experimental results suggest the benefits of employing SHMMs over traditional HMMs.
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