pen-based input, handwriting recognition The accuracy of handwriting recognition is often seen as a key factor in determining the acceptability of hand-held computers that employ a pen for user interaction. We report the results of a study in which the relationship between user satisfaction and recogniser performance was examined in the context of different types of target application. Subjects...

A perturbation model for the generation of synthetic textlines from existing cursively handwritten lines of text produced by human writers is presented. Our goal is to improve the performance of an off-line cursive handwriting recognition system by providing it with additional synthetic training data. It can be expected that by adding synthetic training data the variability of the training set ...

This paper presents a precise system for handwritten Chinese and Japanese character recognition. Before extracting directional element feature (DEF) from each character image, transformation based on partial inclination detection (TPID) is used to reduce undesired effects of degraded images. In the recognition process, city block distance with deviation (CBDD) and asymmetric Mahalanobis distanc...

The objective of this thesis is to investigate the generation and use of synthetic training data for off-line cursive handwriting recognition. It has been shown in many works before that the size and quality of the training data has a great impact on the performance of handwriting recognition systems. A general observation is that the more texts are used for training, the better recognition per...

A model-based approach to on-line cursive handwriting analysis and recognition is presented and evaluated. In this model, on-line handwriting is considered as a modulation of a simple cycloidal pen motion, described by two coupled oscillations with a constant linear drift along the line of the writing. By slow modulations of the amplitudes and phase lags of the two oscillators, a general pen tr...

Being motivated by the widely accepted principle that the more training data we have, the better performance the recognition system has, we conducted experiments asking human subjects to do test on a mixture of real English handwritten textlines and textlines altered from existing handwriting with various distortion degrees. The idea of generating synthetic handwriting is based on a perturbatio...

Semi-continuous Hidden Markov Models (SCHMM) with gaussian distributions are often used in continuous speech or handwriting recognition systems. Our paper compares gaussian and tree-structured polynomial classi ers which have been successfully used in pattern recognition since many years. In our system the binary classi er tree is generated by clustering HMM states using an entropy measure. For...

This paper investigates the cooperation of on-line and off-line handwriting word recognition systems. Our goal is to improve a mature on-line recognition system by exploiting the complementary information present in the off-line representation built from on-line signal. After describing the on-line and off-line HMM based handwriting recognition systems, we propose a formal framework, which allo...

Two brief arguments are made for why handwriting recognition is important. Existing approaches and my approach are summarized along with the stated goals of my project. The full handwriting recognition pipeline of scanning, segmenting, and recognition is examined and described thoroughly in order. Feed forward Artificial Neural Networks are explained on a low level along with their weaknesses a...

Online Chinese handwriting recognition has attracted much research attention recently due to its complexity, wide-spread applications and emerging market demands. This material serves as a guide for pattern recognition researchers who have limited or no background in this language. We provide a brief review of the nature of the problem and challenges of online Chinese handwritten character reco...