We present in this paper an automatic system of handwritten isolated Arabic characters recognition. It is based on a pretopological approach. The approach is based on a criterion constructed from a pretopological pseudo-distance that allows to measure the degree of dissimilarity between the characters. On a database of 6188 handwritten isolated Arabic characters, the experimental results show t...

Handwritten character recognition is always a frontier area of research in the field of pattern recognition and image processing and there is a large demand for OCR on hand written documents. This paper provides a comprehensive review of existing works in handwritten character recognition based on Evolutionary computing technique during the past decade. KeywordsHandwritten Character recognition...

MNIST database serves for comparison of different methods of handwritten digit recognition. There are many data related to different classifier recognition rates among which our neural classifier had the second place [1] (recognition rate 99.21%). At present we develop improvements of neural network structure and algorithms of handwritten digit recognition. Improved classifier has recognition r...

This document describes the application of machine learning algorithms to solving the problem of handwriting recognition. Two models were explored, namely Naïve Bays and Artificial Neural Network, and ANN was found to generate more accurate recognitions. By setting up our model and training on the MNIST database of handwritten digits, we were able to achieve recognition of handwritten digits wi...

OCR is a complicated process, there are many factors that can influence the recognition rate. Early period people tried to optimize the classifier to obtain high recognition rate, but the premise is that there is only one character no matter print or handwritten. For the performance of classifier has been promoted a lot, recognition rate for single character is high enough for commercial use. W...

We consider the problem of recognizing handwritten mathematical content in classroom videos that capture the content written on the whiteboard and the content spoken by the instructor. While the problem of recognizing handwritten textual content from videos has been studied before, recognition of handwritten mathematical content and the use of audio content from classroom videos to assist in re...

The recognition of handwritten digit recognition has been a challenging problem among the researchers for few decades. This paper proposes a relative density feature extraction algorithm for recognizing unconstrained single connected handwritten numerals independent of the languages. The proposed method consists of four phases, namely, image enhancement (dilation), representation (zone based), ...

Successful mathematical handwriting recognition will require recognizers for large sets of handwritten symbols. This paper presents a recognition system for such handwritten mathematical symbols. The recognizer can provide a component of a handwritten interface for computer algebra systems such as Maple. Large sets of similar symbols present new challenges in the area of handwriting recognition...

Handwritten Character Recognition (HCR) is one of the essential aspect in academic and production fields. The recognition system can be either online or offline. There is a large scope for character recognition on hand written papers. India is a multilingual and multi script country, where eighteen official scripts are accepted and have over hundred regional languages. Recognition of unconstrai...