Multi-agent Systems for Arabic Handwriting Recognition

Multi-agent Systems for Arabic Handwriting Recognition

Arabic Handwriting Recognition

This thesis explores a number of different techniques for use in the field of Arabic Handwriting Recognition. A review of previous work in the field is conducted, and then various techniques are explored in the context of classifying town names from the IFN/ENIT database. A baseline-finding algorithm using Principal Components Analysis is implemented, and the change in performance from reducing...

Multi-character Field Recognition for Arabic and Chinese Handwriting

Two methods, Symbolic Indirect Correlation (SIC) and Style Constrained Classification (SCC), are proposed for recognizing handwritten Arabic and Chinese words and phrases. SIC reassembles variable-length segments of an unknown query that match similar segments of labeled reference words. Recognition is based on the correspondence between the order of the feature vectors and of the lexical trans...

Segmentation-Free Online Arabic Handwriting Recognition

Arabic script is naturally cursive and unconstrained and, as a result, an automatic recognition of its handwriting is a challenging problem. The analysis of Arabic script is further complicated in comparison to Latin script due to obligatory dots/stokes that are placed above or below most letters. In this paper, we introduce a new approach that performs online Arabic word recognition on a conti...

Large Vocabulary Arabic Online Handwriting Recognition System

Online handwriting recognition of Arabic script is a difficult problem since it is naturally both cursive and unconstrained. The analysis of Arabic script is further complicated due to obligatory dots/stokes that are placed above or below most letters and usually written delayed in order. In addition, Arabic language is rich in morphology and syntax which makes it a must for a good online handw...