Feature extraction techniques of online handwriting arabic text recognition

• Main Authors: Abuzaraida, Mustafa Ali, Zeki, Akram M., Zeki, Ahmed M.
• Format: Conference or Workshop Item
• Language: English; English
• Published: 2013
• Subjects: QA75 Electronic computers. Computer science; QA76 Computer software; T58.5 Information technology
• Online Access: http://irep.iium.edu.my/30997/1/Table_of_Content.pdf; http://irep.iium.edu.my/30997/2/Feature_Extraction_Techniques_of_Online_Handwriting_Arabic_Text_Recognition1.pdf; http://irep.iium.edu.my/30997/; http://ict4m.org/

Online recognition of Arabic handwritten text has been an ongoing research problem for many years. Generally, online text recognition field has been gaining more interest lately due to the increasing popularity of hand-held computers, digital notebooks and advanced cellular phones. Most of the online text recognition systems consist of three main phases which are preprocessing, feature extraction, and recognition phase. This paper compares between different techniques that have been used to extract the features of Arabic handwriting scripts in online recognition systems. Those techniques attempt to extract the feature vector of Arabic handwritten words, characters, numbers or strokes. This vector then will be fed into the recognition engine to recognize the pattern using the feature vector. The structure and strategy of those reviewed techniques are explained in this article. The strengths and weaknesses of using these techniques will also be discussed.