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|Title||DIC Structural HMM based IWAK-Means to Enclosed Face Data|
This paper identifies two novel techniques for face features extraction based on two different multi-resolution analysis tools; the first called curvelet transform while the second is waveatom transform. The resultant features are trained and tested via three improved hidden Markov Model (HMM) classifiers, such as: Structural HMM (SHMM), Deviance Information Criterion-Inverse Weighted Average K-mean-SHMM (DIC-IWAK-SHMM), and Enclosed Model Selection Criterion (EMC) coupled with DIC-IWAK-SHMM as the proposed methods for face recognition. parallel line, the wavelet multiresolution analysis and HMM were combined in 2003 for face recognition. In this approach a face image is divided into a number of overlapping subimages and wavelet decomposition is performed on each of the subimages, and the performance was better than the original DCT based HMM . A comparative studies for DIC-IWAK-SHMM approach to recognize the face ware achieved by using two type of features; one method using Waveatom features and the other method uses 2-level Curvelet features, these two methods compared with a six methods that used in previous researches. The goal of the paper is twofold; using Deviance information criterion and IWAK-means clustering algorithm based on SHMM. Since HMMs are one-dimensional in nature, many researchers have tried to represent the two dimensional structural. In (2002), a generalization of the embedded hidden Markov models was used for face recognition. An application of the embedded Bayesian networks (EBNs) is presented for face recognition and introduced the improvement of this approach versus the "eigenface" and the embedded HMM approaches . Later in (2003), low-complexity 2D-HMM (LC 2D-HMM) was proposed, which consists of a rectangular constellation of states, where both vertical and horizontal transitions are supported. In (2004), another approach is the 1D discrete HMM (1D-DHMM), which models a face image using two standard HMMs, one for observations in the vertical direction and one for the horizontal direction .
|Published in||International Journal of Computer Applications|
|Series||Volume: 18, Number: 4|
|Publisher||Foundation of Computer Science|
|Item link||Item Link|
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