Title :
Digit/Symbol Pruning and Verification for Arabic Handwritten Digit/Symbol Spotting
Author :
Nobile, Nicola ; He, Chun Lei ; Sagheer, Malik Waqas ; Lam, Louisa ; Suen, Ching Y.
Author_Institution :
Comput. Sci. & Software Eng. Dept., Concordia Univ., Montreal, QC, Canada
Abstract :
In order to spot the digits in a handwritten document, each component is sent to a classifier. This is a time consuming process because a document usually contains several hundred components. A method is presented to reduce the number of candidate components from a handwritten document sent to the classifier. Furthermore, since the classifier does not contain a rejection class, this led to several misclassifications. To lessen this, a verification post processing module was developed in order to reject some false positives. We reached an overall precision of 80% and 83.3% recall on our test set of handwritten documents.
Keywords :
document image processing; image classification; Arabic handwritten digit verification; Arabic symbol spotting; classifier; digit-symbol pruning; handwritten document; verification post processing module; Covariance matrix; Databases; Feature extraction; Handwriting recognition; Helium; Skeleton; Training;
Conference_Titel :
Document Analysis and Recognition (ICDAR), 2011 International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4577-1350-7
Electronic_ISBN :
1520-5363
DOI :
10.1109/ICDAR.2011.136