Handwriting recognition can be a difficult task – while there are many commercial products in place which can be trained for individual users, these programs often have problems abstracting patterns learned in order to work for multiple users. In this work we use the Optical Recognition of Handwritten Digits [3] dataset from the UCI Machine Learning Repository, which contains handwritten digits...

A comparison between the performance of Latin and Arabic handwritten digits recognition problems is presented. The performance of ten different classifiers is tested on two similar Arabic and Latin handwritten digits databases. The analysis shows that Arabic handwritten digits recognition problem is easier than that of Latin digits. This is because the interclass difference in case of Latin dig...