Automatic Discrimination between Confusing Classes with Writing Styles Verification in Arabic Handwritten Numeral Recognition

In handwriting recognition, confusing/conflicting writing styles can result in irreducible errors, so the study of writing style consistencies is important for applications. In Arabic Handwritten Numeral Recognition, most errors occur between samples of classes two and three due to their very similar shapes in some writing styles. In this paper, an automated writing style detection process is effectively implemented in the pair-wise verification of samples in these two classes. As a result, the recognition results have improved significantly with a reduction by 25% of previous errors. With rejection, when the LDA (Linear Discriminant Analysis) measurement rejection threshold is adjusted to maintain the same error rate, the recognition rate increases from 96.87% to 97.81%.