Nowadays, the accurate recognition of machine printed characters is considered largely a solved problem. A lot of commercial products are focused towards that direction, achieving high recognition rates. However, handwritten character recognition is comparatively difficult. So, the recognition of handwritten documents is still a subject of active research. In this thesis we studied the processi...

This paper presents a new approach to off-line handwritten numeral recognition. Recognition of handwritten numerals has been one of the most challenging task in pattern recognition. Recognition of handwritten numerals poses serious problems because of high variability in numeral shapes written by individuals. This paper concerns with offline handwritten numeral recognition based on MLP and SVM ...

Recognition of characters greatly depends upon the features used. Several features of the handwritten Arabic characters are selected and discussed. An off-line recognition system based on the selected features was built. The system was trained and tested with realistic samples of handwritten Arabic characters. Evaluation of the importance and accuracy of the selected features is made. The recog...

Using a novel apparatus coupling a visual illusion with an eye tracker device, trained participants are able to generate smooth pursuit eye movements, even without a target to follow. This allows them to perform arbitrary continuous shapes, and, for instance, write letters with their eyes. In a previous study, based on data from a single writer (author JL), we developed and tested a Bayesian co...

Biometric recognition is still a very difficult task in realworld scenarios wherein unforeseen changes in degradations factors like noise, occlusion, blurriness and illumination can drastically affect the extracted features from the biometric signals. Very recently Haar-like rectangular features which have usually been used for object detection were introduced for biometric recognition resultin...

In this paper, we show that both the writer identification and the writer verification tasks can be carried out using local features such as graphemes extracted from the segmentation of cursive handwriting. We thus enlarge the scope of the possible use of these two tasks which have been, up to now, mainly evaluated on script handwritings. A textual based Information Retrieval model is used for ...

Handwritten text recognition is a problem rarely studied out of specific applications for which lexical knowledge can constrain the vocabulary to a limited one. In the case of handwritten text recognition, additional information can be exploited to characterize the specificity of the writing. This knowledge can help the recognition system to find coherent solutions from both the lexical and the...

Many off–line handwritten word recognition systems have been proposed since the early nineties. Most systems reported high recognition rates, however, they overlooked a very important factor in the process; speed factor. In this paper we explore the potential for speeding up an off–line handwritten word recognition system via concurrency. The goal of the system is to achieve both full accuracy ...

We present in this paper a system of English handwriting recognition based on 40-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, 40-point feature extraction is introduced for extracting the features of the handwritten a...

This paper describes a new feature set for use in the recognition of on-line handwritten Devanagari script based on Fuzzy Directional Features. Experiments are conducted for the automatic recognition of isolated handwritten character primitives (sub-character units). Initially we describe the proposed feature set, called the Fuzzy Directional Features (FDF) and then show how these features can ...