Sub-word based Arabic Handwriting Analysis for Writer Identification

摘要

Analysing a text or part of it is key to handwriting identification. Generally, handwriting is learnt over time and people develop habits in the style of writing. These habits are embedded in special parts of handwritten text. In Arabic each word consists of one or more sub-word(s). The end of each sub-word is considered to be a connect stroke. The main hypothesis in this paper is that sub-words are essential reflection of Arabic writer's habits that could be exploited for writer identification. Testing this hypothesis will be based on experiments that evaluate writer's identification, mainly using K nearest neighbor from group of sub-words extracted from longer text. The experimental results show that using a group of sub-words could be used to identify the writer with a successful rate between 52.94 % to 82.35% when top l is used, and it can go up to 100% when top5 is used based on K nearest neighbor. The results show that majority of writers are identified using 7 sub-words with a reliability confident of about 90% (i.e. 90% of the rejected templates have significantly larger distances to the tested example than the distance from the correctly identified template). However previous work, using a complete word, shows successful rate of at most 90% in top 10.