Title :
Noise Tolerant Script Identification of Printed Oriental and English Documents Using a Downgraded Pixel Density Feature
Author :
Wang, Ning ; Lam, Louisa ; Suen, Ching Y.
Author_Institution :
Centre for Pattern Recognition & Machine Intell., Concordia Univ., Montreal, QC, Canada
Abstract :
Document Script Identification (DSI) is a very useful application in document processing. This paper presents a method for this application that uses a new noise tolerant feature, the Downgraded Pixel Density feature. Compared to other features widely used in existing DSI solutions, this new feature is much more robust to variations in slant, font and style of printed documents. Experimental results show that the method achieves promising identification performances.
Keywords :
document image processing; feature extraction; natural language processing; DSI; document processing; document script identification; downgraded pixel density feature; noise tolerant feature; noise tolerant script identification; printed English documents; printed oriental documents; Artificial neural networks; Databases; Feature extraction; Pixel; Principal component analysis; Support vector machines; Training; document analysis; downgraded pixel density feature; script identification;
Conference_Titel :
Pattern Recognition (ICPR), 2010 20th International Conference on
Conference_Location :
Istanbul
Print_ISBN :
978-1-4244-7542-1
DOI :
10.1109/ICPR.2010.502
