Handwriting is an important modality for Human-Computer Interaction. For medical professionals, handwriting is (still) the preferred natural method of documentation. Handwriting recognition has long been a primary research area in Computer Science. With the tremendous ubiquity of smartphones, along with the renaissance of the stylus, handwriting recognition has become a new impetus. However, re...

-------------------------------------------------------------ABSTRACT-------------------------------------------------------Biometric Technologies are automated methods for verifying or recognizing the identity of a living person based on physiological or behavioral characteristics. Multimodal Biometric Systems are those which utilize more than one physiological or behavioral characteristic for...

The study of the link between handwriting and personality is known as analysis. It a specific manner using to convey one’s cognitive process. That’s why it’s also “brain writing”. Handwriting, like person’s fingerprint, unique trait that cannot be duplicated by two distinct people. aids us in determining emotional state. Handwriting recognition usually done traditional manner, which professiona...

The process of transcribing a language represented in its spatial form graphical characters into symbolic representation is called handwriting recognition. Each script has collection or letters, often known as symbols, that all share the same fundamental shapes. Handwriting analysis aims to correctly identify input images before being analysed by various automated systems. Recent research image...

In pattern recognition there is a variety of applications where the patterns are classi ed using edit distance. In this paper we present some results comparing the use of tree and string edit distances in a handwritten character recognition task. Some experiments with di erent number of classes and of classi ers are done.

Handwriting recognition systems rely on predefined classifiers. Small and static dictionaries are usually exploited to obtain high in-vocabulary (IV) accuracy at the expense of coverage. Thus the recognition of out-of-vocabulary (OOV) words cannot be handled efficiently. To improve OOV recognition while keeping IV dictionaries small, we introduce a multi-step approach that exploits Web resource...

The automatic handwriting identification is a hot topic in pattern recognition that it has been extensively studied in many languages. A Uyghur handwriting identification technique based on the stroke statistical features is proposed in this paper. Firstly, the handwriting image is preprocessed taking modified methods of grid line removal, noise reduction and thinning. Then novel stroke statist...

Online handwriting recognition of Arabic script is a difficult problem since it is naturally both cursive and unconstrained. The analysis of Arabic script is further complicated in comparison to Latin script due to obligatory dots/stokes that are placed above or below most letters. This paper introduces a Hidden Markov Model (HMM) based system to provide solutions for most of the difficulties i...

This communication investigates the automatic reading of unconstrained omni-writer handwritten texts. It shows how to endow the reading system with learning faculties necessary to adapt the recognition to each writer’s handwriting. In the first part of this communication, we explain how the recognition system can be adapted to a current handwriting by exploiting the graphical context defined by...

In this paper we present a new database for off-line handwriting recognition, together with a few preprocessing and text segmentation procedures. The database is based on the Lancaster-Oslo/Bergen(LOB) corpus. This corpus is a collection of texts that were used to generate forms, which subsequently were filled out by persons with their handwriting. Up to now (December 1998) the database include...