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» A Statistical Learning Approach To Document Image Analysis
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ICDAR
2003
IEEE
14 years 20 days ago
An Approach to Extracting the Target Text Line from a Document Image Captured by a Pen Scanner
In this paper, we present a new approach to extracting the target text line from a document image captured by a pen scanner. Given the binary image, a set of possible text lines a...
Zhen-Long Bai, Qiang Huo
ICIP
2005
IEEE
14 years 9 months ago
Learning to binarize document images using a decision cascade
In this article, we propose a special type of decision tree, called a decision cascade, for binarizing document images. Such images are produced by cameras, resulting in varying de...
Chien-Hsing Chou, Chih-Ching Huang, Wen-Hsiung Lin...
ICDAR
2009
IEEE
14 years 2 months ago
Enhanced Text Extraction from Arabic Degraded Document Images Using EM Algorithm
This paper presents a new enhanced text extraction algorithm from degraded document images on the basis of the probabilistic models. The observed document image is considered as a...
Wafa Boussellaa, Aymen Bougacha, Abderrazak Zahour...
ICASSP
2011
IEEE
12 years 11 months ago
Denoising of image patches via sparse representations with learned statistical dependencies
We address the problem of denoising for image patches. The approach taken is based on Bayesian modeling of sparse representations, which takes into account dependencies between th...
Tomer Faktor, Yonina C. Eldar, Michael Elad
ICDAR
1999
IEEE
13 years 11 months ago
Region Description and Comparative Analysis using a Tesseral Representation
This paper presents a region-representation scheme and comparative analysis methods based on a tesseral addressing system. The proposed scheme is described in the context of perfo...
Apostolos Antonacopoulos, Frans Coenen