In the modern times identity verification has become an important task for various reasons. Mostly identity provided by the authorities is the combination of characters & digits. Now there are several techniques available to recognize them efficiently, & good accuracy rates also have been achieved for characters & digits recognition (Typewritten).But in case of handwritten characters, accuracy ...

This paper presents an insight into the state-of-art in handwriting recognition systems and describes the evolution and progress in the field. An in-depth literature survey of Indic script recognition systems for Bangla, Devnagari, Gurumukhi, Kannada, Malayalam, tamil, and Urdu is presented. This study focuses on multitude of feature and classification techniques giving an insight into the effi...

A method for preclassification of handwritten Chinese characters is presented. A set of basic stroke substructures is defined using the consistent stroke connection relations. A knowledge guided recognition process is employed to identify the types of the extracted basic stroke substructures found in a handwritten character. Then a 1-D character coding scheme is given to represent the character...

-Arabic script based languages character recognition remains a challenging task due to its cursive nature. This task becomes more complex and demanding in case of handwritten Arabic script. We have used two layers HMM for recognition. We extracted directional and structural features for handwritten stroke and fused these feature to form more discriminant feature matrix. The fused feature matrix...

There are several problems in pattern recognition system like feature extraction problem and identification, pre-processing and classification problem etc. One of the application domains in pattern classification is handwritten character or symbolic recognition. Identifying handwritten characters is always a complex and challenging task for the researchers. Wide research has been done on the ch...

In this study, we introduce a set of one-dimensional features to represent two dimensional shape information for HMM (Hidden Markov Model) based handwritten optical character recognition problem. The proposed feature set embeds two-dimensional information into an observation sequence of one-dimensional string, selected from a code-book. It provides a consistent normalization among distinct clas...

The Character recognition is one of the most important areas in the field of pattern recognition. Recently Indian Handwritten character recognition is getting much more attention and researchers are contributing a lot in this field. But Malayalam, a South Indian language has very less works in this area and needs further attention. Malayalam OCR is a complex task owing to the various character ...

Several approaches to recognize the handwritten characters and numerals such as online cursive handwriting and numerals recognition have been proposed. Most of them are based on neural network approaches. In this paper, a technique for continuous recognition of handwritten Devanagari characters is proposed. This approach employs a method based on Spatio-Temporal Artificial Neural Network (STANN...

Gurumukhi script is used for Punjabi language, which is a two dimensional composition of symbols with connected and disconnected diacritics. Handwritten Gurumukhi script has some complexities like connected, overlapped text lines, words and characters. It is one of the foremost issues for errors during the recognition process. Text segmentation is a challenging job in unconstrained writer indep...

This paper proposes a statistical-structural character learning algorithm based on hidden Markov model for handwritten Nushu character recognition. The stroke relationships of a Nushu character reflect its structure, which can be statistically represented by the hidden markov model. Based on the prior knowledge of character structures, we design an adaptive statisticalstructural character learn...