This paper presents an effective method for writer recognition in handwritten documents. We have introduced a set of features that are extracted from two different representations of the contours of handwritten images. These features mainly capture the orientation and curvature information at different levels of observation, first from the chain code sequence of the contours and then from a set...

Off-line recognition of text play a significant role in several application such as the automatic sorting of postal mail or editing old documents. It is the ability of the computer to distinguish characters and words. Automatic off-line recognition of text can be divided into the recognition of printed and handwritten characters. Off-line Arabic handwriting recognition still faces great challen...

in this paper, we used a shape matching algorithm to recognize farsi digits. for each sampled point on the contour of a shape, we obtain a descriptor showing the distribution of the other points of the contour, with respect to this point. based on these descriptors, we find the corresponding points of the two contours and take the sum of their distances as a dissimilarity measure between two sh...

This paper describes the design of an online handwritten characters recognition server. Currently, fast and accurate recognition of online handwritten characters requires a high-performance CPU and a large memory space. However, PDA and other small portable devices lack the qualification. To solve this problem, we employ a network environment and build an on-line handwritten characters recognit...

We present in this paper a system of English handwriting recognition based on 26-point feature extraction of the character. Basically an off-line handwritten alphabetical character recognition system using multilayer feed forward neural network has been described in our work. Firstly a new method, called, 26-point feature extraction is introduced for extracting the features of the handwritten a...

The recognition of handwritten digits is an application which has been used as a benchmark for comparing shape recognition methods. We train COSFIRE filters to be selective for different parts of handwritten digits. In analogy with the neurophysiological concept of population coding we use the responses of multiple COSFIRE filters as a shape descriptor of a handwritten digit. We demonstrate the...

We further investigate the problem of recognizing handwritten mathematical expressions, which we also chose for our CS221 final project [3]. Being able to change handwritten expressions into LATEX has applications for consumers and academics. While large amounts of work have been done for digit and character recognition [2] [10], much less progress has been made surrounding handwritten expressi...

Entering mathematical queries, in general, can be a demanding task. Mathematical notation is twodimensional and cannot be easily typed with a standard QWERTY keyboard. Handwriting appears to be the most intuitive and promising method to express mathematical queries. Recognition technology for handwritten mathematical notation has never been applied in math search. Existing recognition technique...