This research investigates innovations for the computer transcription of handwritten Pitman’s Shorthand as a rapid means of text entry (up to 100 words per minute) into today’s pen-based handheld devices. Two mathematical models are developed in this work. The first model deals with high level phonetic-based translation, while the second model is specifically concerned with low level primitive-...

This paper describes an off-line system under development to process unconstrained handwritten dates on Brazilian bank cheques in an omni-writer context. We show here some improvements on our previous work on isolated month word recognition using Hidden Markov Models (HMMs). After preprocessing, a word image is explicitly segmented into characters or pseudo-characters and represented by two fea...

A hidden Markov model (HMM) based continuous speech recognition system is applied to on-line cursive handwriting recognition. The base system is unmodified except for using handwriting feature vectors instead of speech. Due to inherent properties of HMMs, segmentation of the handwritten script sentences is unnecessary. A 1.1% word error rate is achieved for a 3050 word lexicon, 52 character, wr...

This paper 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 2rst part of this paper, we explain how the recognition system can be adapted to a current handwriting by exploiting the graphical context de2ned by the writer’s inva...

There are many difficulties facing a handwritten Arabic recognition system such as unlimited variation in human handwriting, similarities of distinct character shapes, interconnections of neighbouring characters and their position in the word. The typical Optical Character Recognition (OCR) systems are based mainly on three stages, preprocessing, features extraction and recognition. This paper ...

Handwriting recognition is considered a very hard area of research, especially for Arabic, because its ligatures, cursive nature, diacritics, and overlapping. Although many studies have been conducted on Arabic recognition, this field still has unsolved problems. This work aims to provide comprehensive review various strategies handling handwriting recognition. Furthermore, it details general c...

Off-line recognition of text plays a significant role in several applications such as the automatic sorting of postal mail or editing old documents. The recognition of Arabic handwriting characters is a difficult task owing to the similar appearance of some different characters. Most researchers have presented methods that recognise isolated characters. However, recognition of all shapes of Ara...

There are many connected characters in cursive Uyghur handwriting, which makes the segmentation and recognition of Uyghur words very difficult. To enable large vocabulary Uyghur word recognition using character models, we propose a character separation method for over-segmentation in online cursive Uyghur handwriting. After removing delayed strokes from the handwritten words, potential breakpoi...

Computer handwriting recognition ooers a new way of improving the human-computer interface and of enabling computers to read and process the many handwritten documents that must currently be processed manually. This thesis describes the design of a system that can transcribe handwritten documents. First, a review of the aims and applications of computer handwriting recognition is presented, fol...