The process of transcribing a language represented in its spatial form graphical characters into symbolic representation is called handwriting recognition. Each script has collection or letters, often known as symbols, that all share the same fundamental shapes. Handwriting analysis aims to correctly identify input images before being analysed by various automated systems. Recent research image...

Handwritten digit recognition is an open problem in computer vision and pattern recognition, and solving this problem has elicited increasing interest. The main challenge of this problem is the design of an efficient method that can recognize the handwritten digits that are submitted by the user via digital devices. Numerous studies have been proposed in the past and in recent years to improve ...

Arabic script is the third most widely used writing system after Latin and Chinese, but research in Arabic Optical Character Recognition (OCR) is still nascent in comparison to Latin script. Arabic script is inherently cursive in nature, therefore techniques developed for other scripts are generally inappropriate for Arabic. In this paper we present recent progress in the field of Handwritten A...

Off-line handwriting recognition deals with the task of automatically recognizing handwritten text from images, for example from scanned sheets of paper. Due to the tremendous variations of writing styles encountered between different individuals, this is a very challenging task. Traditionally, a recognition system is trained by using a large corpus of handwritten text that has to be transcribe...

In dealing with the problem of recognition of handwritten character patterns of varying shapes and sizes, selection of a proper feature set is important to achieve high recognition performance. The current research aims to evaluate the performance of the convex hull based feature set, i.e. 125 features in all computed over different bays attributes of the convex hull of a pattern, for effective...