Title :
Arabic (Indian) handwritten digits recognition using Gabor-based features
Author :
Mahmoud, Sabri A.
Author_Institution :
Inf. & Comput. Sci., King Fahd Univ. of Pet. & Miner., Dhahran
Abstract :
Arabic (Indian) handwritten digits recognition is useful in a large variety of banking and business applications and in postal zip code reading, and data entry applications. In this paper we present a technique for the automatic recognition of Arabic (Indian) handwritten digits using Gabor-based features and support vector machines (SVMs). A database consisting of 21120 samples written by 44 writers is used. 70% of the data is used for training and the remaining 30% is used for testing. Several scales and orientations are used to extract the Gaborbased features. The achieved average recognition rates are 99.85% and 97.94% using 3 scales & 5 orientations and using 4 scales & 6 orientations, respectively. The experimental results indicate the effectiveness of the Gabor-based features and SVM for Arabic (Indian) digits recognition.
Keywords :
Gabor filters; handwritten character recognition; natural language processing; support vector machines; Arabic handwritten digits recognition; Gabor-based features; Indian handwritten digits recognition; data entry; postal zip code reading; support vector machines; Application software; Banking; Computer science; Feature extraction; Gabor filters; Handwriting recognition; Hidden Markov models; Image segmentation; Petroleum; Support vector machines; Arabic (Indian) digits; Gabor filters; Recognition of handwritten Arabic numerals; Support Vector Machines;
Conference_Titel :
Innovations in Information Technology, 2008. IIT 2008. International Conference on
Conference_Location :
Al Ain
Print_ISBN :
978-1-4244-3396-4
Electronic_ISBN :
978-1-4244-3397-1
DOI :
10.1109/INNOVATIONS.2008.4781779