Hidden Markov Model (HMM) is a stochastic method which has been used in various signal processing and character recognition. This study proposes to use HMM to recognize Javanese characters from a number of different handwritings, whereby HMM is used to optimize the number of state and feature extraction. An 85.7 % accuracy is obtained as the best result in 16-stated vertical model using pure HMM. This initial result is satisfactory for prompting further research
In this paper, we compare the experimental results for Tamil online handwritten character recognitio...
In this paper, we compare the experimental results for Tamil online handwritten character recognitio...
Abstract. A novel, fast feature selection method for hidden Markov model (HMM) based classifiers is ...
Handwritten character recognition plays an important role in the modern world. It can solve more com...
Recognition rate of handwritten character is still limited around 90 percent due to the presence of ...
ABSTRACT This paper presents a recognition system for Arabic handwritten isolated characters. The re...
A method is described for representing character images which involves the extraction of features fr...
A method is described for representing character images which involves the extraction of features fr...
Hidden Markov models are used to model the generation of handwritten, isolated characters. Models ar...
In this paper, we propose a system for recognition handwritten characters Tifinagh, with the use of ...
Abstract- Recognition rate of handwritten character is still limited due to presence of large variat...
Abstract: Intense research is being carried in the field of character recognition.There are many way...
Sundanese language is one of the popular languages in Indonesia. Thus, research in Sundanese languag...
The wide area of the application of HMM is in Speech Recognition where each spoken word is considere...
Handwriting recognition is a main topic of Optical Character Recognition (OCR), which has a very wid...
In this paper, we compare the experimental results for Tamil online handwritten character recognitio...
In this paper, we compare the experimental results for Tamil online handwritten character recognitio...
Abstract. A novel, fast feature selection method for hidden Markov model (HMM) based classifiers is ...
Handwritten character recognition plays an important role in the modern world. It can solve more com...
Recognition rate of handwritten character is still limited around 90 percent due to the presence of ...
ABSTRACT This paper presents a recognition system for Arabic handwritten isolated characters. The re...
A method is described for representing character images which involves the extraction of features fr...
A method is described for representing character images which involves the extraction of features fr...
Hidden Markov models are used to model the generation of handwritten, isolated characters. Models ar...
In this paper, we propose a system for recognition handwritten characters Tifinagh, with the use of ...
Abstract- Recognition rate of handwritten character is still limited due to presence of large variat...
Abstract: Intense research is being carried in the field of character recognition.There are many way...
Sundanese language is one of the popular languages in Indonesia. Thus, research in Sundanese languag...
The wide area of the application of HMM is in Speech Recognition where each spoken word is considere...
Handwriting recognition is a main topic of Optical Character Recognition (OCR), which has a very wid...
In this paper, we compare the experimental results for Tamil online handwritten character recognitio...
In this paper, we compare the experimental results for Tamil online handwritten character recognitio...
Abstract. A novel, fast feature selection method for hidden Markov model (HMM) based classifiers is ...