<?xml version="1.0" encoding="UTF-8"?> <article key="pdf/274" mdate="2008-06-23 00:00:00"> <author>Ahmad T. Al-Taani</author> <title>An Efficient Feature Extraction Algorithm for the Recognition of Handwritten Arabic Digits</title> <pages>2221 - 2225</pages> <year>2008</year> <volume>2</volume> <number>6</number> <journal>International Journal of Computer and Information Engineering</journal> <ee>https://publications.waset.org/pdf/274</ee> <url>https://publications.waset.org/vol/18</url> <publisher>World Academy of Science, Engineering and Technology</publisher> <abstract>In this paper, an efficient structural approach for recognizing online handwritten digits is proposed. After reading the digit from the user, the slope is estimated and normalized for adjacent nodes. Based on the changing of signs of the slope values, the primitives are identified and extracted. The names of these primitives are represented by strings, and then a finite state machine, which contains the grammars of the digits, is traced to identify the digit. Finally, if there is any ambiguity, it will be resolved. Experiments showed that this technique is flexible and can achieve high recognition accuracy for the shapes of the digits represented in this work.</abstract> <index>Open Science Index 18, 2008</index> </article>