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On the structure of hidden Markov models

K.T. Abou-Moustafa, M. Cheriet, C.Y. Suen
2004 Pattern Recognition Letters  
This paper investigates the effect of HMM structure on the performance of HMM-based classifiers.  ...  The investigation is based on the framework of graphical models, the diffusion of credits of HMMs and empirical experiments.  ...  Acknowledgements We would like to thank Incheol Kim from CENPARMI for useful discussions.  ... 
doi:10.1016/j.patrec.2004.02.005 fatcat:kjxinwhrzfddpdm5nxe2xgsazm

Hidden Markov Model Based Odia Numeral Recognition Using Moment and Structural Features

2019 International Journal of Engineering and Advanced Technology  
In our proposed method we have developed an efficient recognition algorithm using Hidden Markov model based on moment based and structural feature to recognize Odia characters and numerals.  ...  Hidden Markov Model have many advantages such as resistant to noise, handle contrast recorded as a hard copy and the HMM devices are effectively accessible.  ...  HIDDEN MARKOV MODEL HMM model is statistical model with unobserved state or hidden state. Mainly HMM used in speech, character recognition.  ... 
doi:10.35940/ijeat.f8614.088619 fatcat:elnwa757pfantlhccsfprt7fsu

Designing the Minimal Structure of Hidden Markov Model by Bisimulation [chapter]

Manuele Bicego, Agostino Dovier, Vittorio Murino
2001 Lecture Notes in Computer Science  
Hidden Markov Models (HMMs) are an useful and widely utilized approach to the modeling of data sequences.  ...  application.  ...  Introduction Hidden Markov Models (HMMs) represent a widespread approach to the modeling of sequences: they attempt to capture the underlying structure of a set of symbol strings.  ... 
doi:10.1007/3-540-44745-8_6 fatcat:vll3sjpiobdg7cs2dpv32yqdpu

Structural Hidden Markov Models Using a Relation of Equivalence: Application to Automotive Designs

D. Bouchaffra, J. Tan
2006 Data mining and knowledge discovery  
The results reported in this application show that SHMM's outperform the traditional hidden Markov model with a 9% of increase in accuracy.  ...  We propose in this paper a novel paradigm that we named "structural hidden Markov model" (SHMM).  ...  We are also grateful to all students from Oakland University who spent a part of their time to answer our questions during this survey.  ... 
doi:10.1007/s10618-005-0020-8 fatcat:bntxbua5rvbjhk4l5cingw4kai

Embedding HMMs-based models in a Euclidean space: the topological hidden Markov models

Djamel Bouchaffra
2010 Pattern Recognition  
We have applied the concept of THMM's to: (i) predict the ASCII class assigned to a handwritten numeral, and (ii) map a protein primary structure to its 3D fold.  ...  To fulfill this need, we propose a novel paradigm named "topological hidden Markov models" (THMM's) that classifies VO sequences by embedding the nodes of an HMM state transition graph in a Euclidean space  ...  Introduction The real milestone of the hidden Markov models (HMM's) occurred when applied to speech recognition in the late 1980's [8] .  ... 
doi:10.1016/j.patcog.2010.01.022 fatcat:ifmwkjzoyvhnjakgs5a4vyswya

An Efficient Hidden Markov Model for Offline Handwritten Numeral Recognition [article]

B. S. Saritha, S. Hemanth
2010 arXiv   pre-print
The ability to identify machine printed characters in an automated or a semi automated manner has obvious applications in numerous fields.  ...  Nowadays, although recognition of printed isolated characters is performed with high accuracy, recognition of handwritten characters still remains an open problem in the research arena.  ...  It is felt that, finding additional hidden unique features in the numeral can further increase the recognition rate.  ... 
arXiv:1001.5334v1 fatcat:ddzpoxefmjgtfpzx6oabr7vjle

Markov models for offline handwriting recognition: a survey

Thomas Plötz, Gernot A. Fink
2009 International Journal on Document Analysis and Recognition  
It is therefore the goal of this survey to provide a comprehensive overview of the application of Markov models in the research field of offline handwriting recognition, covering both the widely used hidden  ...  The recognition of handwriting can, however, still be considered an open research problem due to its substantial variation in appearance.  ...  "Simple structure -lots of parameters" Similar to alternative application domains of hidden Markov models (cf. speech recognition tasks or bioinformatics applications) model topologies of HMMs that are  ... 
doi:10.1007/s10032-009-0098-4 fatcat:el2rdqroj5dp3bfuvzs2bwx2bm

Online handwriting Farsi character and number recognition based on hand movement direction using Hidden Markov Models

Zohre Sadrnezhad, Atefeh Nekouie, Majid Vafaei Jahan
2014 2014 International Congress on Technology, Communication and Knowledge (ICTCK)  
In this paper, we introduce a method for online handwriting Farsi character and number recognition using Hidden Markov Models (HMM).  ...  Keywords- Baum-Welch algorithm; Forward algorithm; online handwriting Farsi character and numbers recognition; Hidden Markov Model (HMM) I.  ...  There are different methods for handwriting recognition, including statistical methods such as Hidden Markov Models and structural methods such as Neural Networks.  ... 
doi:10.1109/ictck.2014.7033518 fatcat:xeqovvkluzdvrccxzibthqoebq

Construction of Statistical SVM based Recognition Model for Handwritten Character Recognition

Yasir Babiker Hamdan, Sathish
2021 Journal of Information Technology and Digital World  
There are many applications of the handwritten character recognition (HCR) approach still exist.  ...  The proposed model has tested on a training section that contained various stylish letters and digits to learn with a higher accuracy level.  ...  In many research articles, a system for recognition of offline cursive handwriting was described, based on Hidden Markov (HMM) models by using hybrid models [4] .  ... 
doi:10.36548/jitdw.2021.2.003 fatcat:iyazn7w2vbajhenb2nkq3eqavi

Developing pattern recognition systems based on Markov models: The ESMERALDA framework

G. A. Fink, T. Plötz
2008 Pattern Recognition and Image Analysis  
ESMERALDA primarily supports continuous density Hidden Markov Models (HMMs) of different topologies and with user-definable internal structure.  ...  In this paper we describe ESMERALDA -an integrated Environment for Statistical Model Estimation and Recognition on Arbitrary Linear Data Arrays -which is a framework for building statistical recognizers  ...  University, Bielefeld, Germany, and the significant contributions to the image processing module by Marc Hanheide and Frank Lömker.  ... 
doi:10.1134/s1054661808020041 fatcat:hvagbnvfrzfmlkgstfgq6o4ylu

Postprocessing of recognized strings using nonstationary Markovian models

D. Bouchaffra, V. Govindaraju, S.N. Srihari
1999 IEEE Transactions on Pattern Analysis and Machine Intelligence  
Index TermsÐNonstationary hidden Markov models, zip code recognition, postprocessing, class conditional probability, Markov random fields.  ...  An especially interesting facet of the model is its ability to excite and inhibit certain positions in the n-grams leading to the familiar area of Markov Random Fields.  ...  Other methods using a hidden Markov model to scan the entire string and extract feature vectors to perform recognition have also been proposed [9] .  ... 
doi:10.1109/34.799906 fatcat:r6sxh77l7nhwzo2dourrercbbu

Hidden Markov models with spectral features for 2D shape recognition

Jinhai Cai, Zhi-Qiang Liu
2001 IEEE Transactions on Pattern Analysis and Machine Intelligence  
To demonstrate the effectiveness of our models, we have tested our methods on two image databases: hand-tools and unconstrained handwritten numerals.  ...  We develop algorithms for reestimating parameters of hidden Markov models.  ...  ACKNOWLEDGMENTS The authors would like to thank Stan Sclaroff of the Department of Computer Science, Boston University, for granting them the permission to use the database of hand tool images.  ... 
doi:10.1109/34.977569 fatcat:iazdg3772jabro6fobw5ormbe4

Performance of hidden Markov model and dynamic Bayesian network classifiers on handwritten Arabic word recognition

Jawad H. AlKhateeb, Olivier Pauplin, Jinchang Ren, Jianmin Jiang
2011 Knowledge-Based Systems  
This paper presents a comparative study of two machine learning techniques for recognizing handwritten Arabic words, where hidden Markov models (HMMs) and dynamic Bayesian networks (DBNs) were evaluated  ...  In order to validate the techniques, extensive experiments were conducted using the IFN/ENIT database which contains 32,492 Arabic words.  ...  Actually, HMM is an excellent in classifying Arabic handwritten words. The system has been applied to the well-known IFN/ENIT database containing handwriting words written by different writers.  ... 
doi:10.1016/j.knosys.2011.02.008 fatcat:7vsaehnaq5hvnclekd5sjnspde

Google PageRank Algorithm: Markov Chain Model and Hidden Markov Model

Prerna Rai, Arvind Lal
2016 International Journal of Computer Applications  
The basic algorithm used by Google, for PageRanking and other applications are Markov model or Markov Chain model and Hidden Markov model.  ...  Markov chain model and Hidden Markov model is a mathematical system model. It describes transitions from one state to another in a state space.  ...  Markov Chain Model Hidden Markov Model.  ... 
doi:10.5120/ijca2016908942 fatcat:pzdiqg7vwnd3zmxbyqkhogklbq

Hidden Markov models applied to on-line handwritten isolated character recognition

S.R. Veltman, R. Prasad
1994 IEEE Transactions on Image Processing  
Hidden Markov Models Applied to On-Line Handwritten Isolated Character Recognition Stephan R.  ...  Veltman and Ramjee Prasad, Senior Member, IEEE Abs-t-Hidden Markov models are used to model the generalion of handwritten, isolated characters.  ... 
doi:10.1109/83.287027 pmid:18291931 fatcat:vilr3bowtvhhhjmfq233awm5ly
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