DocumentCode
398590
Title
Iterative sub-image binarization for document images
Author
Dawoud, A. ; Kamel, Michel
Author_Institution
Dept. of Syst. Design Eng., Waterloo Univ., Ont., Canada
Volume
1
fYear
2003
fDate
14-17 Sept. 2003
Abstract
Existing binarization methods are categorized as either global or local. In this paper we present a new category, where the image is considered as a collection of sub-images. Each sub-image provides a statistical model for the handwritten characters that will be used to optimize the binarization of other sub-images. This method can be applied to different types of documents and doesn´t require any prior knowledge about the noisiness of the sub-images.
Keywords
document image processing; feature extraction; handwritten character recognition; optimisation; document images; feature extraction; handwritten characters; iterative sub-image binarization; optimisation; statistical model; Background noise; Computed tomography; Feature extraction; Gray-scale; Histograms; Interference elimination; Pixel; Statistical analysis; Statistical distributions; Writing;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing, 2003. ICIP 2003. Proceedings. 2003 International Conference on
ISSN
1522-4880
Print_ISBN
0-7803-7750-8
Type
conf
DOI
10.1109/ICIP.2003.1247021
Filename
1247021
Link To Document