A Statistical Multiresolution Approach for Face Recognition Using Structural Hidden Markov Models

Speaker Independent Speech Recognition Using Hidden Markov Models for Persian Isolated Words

Speaker Independent Speech Recognition Using Hidden Markov Models for Persian Isolated Words

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 CriterionInverse Weighted Average K-...

An Adaptive Approach to Increase Accuracy of Forward Algorithm for Solving Evaluation Problems on Unstable Statistical Data Set

Nowadays, Hidden Markov models are extensively utilized for modeling stochastic processes. These models help researchers establish and implement the desired theoretical foundations using Markov algorithms such as Forward one. however, Using Stability hypothesis and the mean statistic for determining the values of Markov functions on unstable statistical data set has led to a significant reducti...

Combining Wavelets with HMM for Face Recognition

This paper describes face recognition algorithms that improve upon the original DCT based HMM face recogniser by using wavelet multiresolution analysis to extract observation sequences . In this approach a face image is divided into a number of overlapping subimages and wavelet decomposition is performed on each of the subimages. The ORL and our own face databases are used to test the algorithm...