In this article, we propose a numerical field extraction system from unconstrained handwritten documents. The system is based on a segmentation driven by recognition stage followed by a syntactical analysis which detects the sequences that may compose a numerical field. We focus here on the design of a digit classifier embedded in the segmentation/recognition process able to discriminate digits...

This paper will emphasize the necessity of having alternative man-machine interfaces to the already established keyboard and mouse, speciically for people residing in developing countries. An on-line system is presented for recognizing handwritten Farsi (Persian) and Arabic digits. This recognition scheme is based on statistical techniques which will be brieey explained. Then, the grounds will ...

This paper presents an original hybrid MLP-SVM method for unconstrained handwritten digits recognition. Specialized Support Vector Machines (SVMs) are introduced to improve significantly the MLP performances in local areas around the separation surfaces between each pair of digit classes, in the input pattern space. This hybrid architecture is based on the idea that the correct digit class almo...

A simple method based on some statistical measurements for Latin handwritten digit recognition is proposed in this paper. Firstly, a preprocess step is started with thresholding the gray-scale digit image into a binary image, and then noise removal, spurring and thinning are performed. Secondly, by reducing the search space, the region-of-interest (ROI) is cropped from the preprocessed image, t...

Recently, an increasing number of studies have applied deep learning algorithms for extracting information from handwritten historical documents. In order to accomplish that, documents must be divided into smaller parts. Page and line segmentation are vital stages in the Handwritten Text Recognition systems; it directly affects character stage, which turn determines recognition success. this st...

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In this review paper we are going to discuss a systematic trajectory recognition algorithm framework that can construct effective classifiers for hand writing & gesture identification. Review of Digital Pen for Handwritten Digit and Gesture Recognition using Trajectory Recognition Algorithm based on Accelerometer is discuss for the identification of 2-D handwriting digits and 3-D hand gestures....

Classification Ensemble, which uses the weighed polling of outputs, is the art of combining a set of basic classifiers for generating high-performance, robust and more stable results. This study aims to improve the results of identifying the Persian handwritten letters using Error Correcting Output Coding (ECOC) ensemble method. Furthermore, the feature selection is used to reduce the costs of ...

Offline Arabic handwriting character recognition (AHCR) systems are very important since they make life easier for governments, researchers and scholars who are dealing with Arabic language in education, documentation and security. A widening use of the Arabic script in countries that deals with the Arabic language and countries that use the Arabic script in their languages such as Persian and ...