Title :
Recognition-Based Segmentation Algorithm for On-Line Arabic Handwriting
Author :
Daifallah, Khaled ; Zarka, Nizar ; Jamous, Hassan
Author_Institution :
Fac. of Inf. Technol. Eng., Damascus Univ., Damascus, United Arab Emirates
Abstract :
In this paper, we introduce an on-line Arabic handwritten recognition system based on new stroke segmentation algorithm. The proposed algorithm uses an over segmentation method that has the advantage of giving all correct segments at least. It is based on arbitrary segmentation followed by segmentation enhancement, consecutive joints connection and finally segmentation point locating. The proposed system gives an excellent recognition rate up to 97% and 92% for words and letter recognition.
Keywords :
handwriting recognition; handwritten character recognition; image enhancement; image recognition; image segmentation; online Arabic handwritten recognition system; segmentation enhancement; stroke segmentation algorithm; Algorithm design and analysis; Character recognition; Feature extraction; Handwriting recognition; Hidden Markov models; Information analysis; Information technology; Natural languages; Testing; Text analysis; HMM; On-Line Arabic Handwriting; Recognizing; Segmentation;
Conference_Titel :
Document Analysis and Recognition, 2009. ICDAR '09. 10th International Conference on
Conference_Location :
Barcelona
Print_ISBN :
978-1-4244-4500-4
Electronic_ISBN :
1520-5363
DOI :
10.1109/ICDAR.2009.169
