Title
A model for the gray-intensity distribution of historical handwritten documents and its application for binarization
Abstract
In this article, our goal is to describe mathematically and experimentally the gray-intensity distributions of the fore- and background of handwritten historical documents. We propose a local pixel model to explain the observed asymmetrical gray-intensity histograms of the fore- and background. Our pixel model states that, locally, the gray-intensity histogram is the mixture of gray-intensity distributions of three pixel classes. Following our model, we empirically describe the smoothness of the background for different types of images. We show that our model has potential application in binarization. Assuming that the parameters of the gray-intensity distributions are correctly estimated, we show that thresholding methods based on mixtures of lognormal distributions outperform thresholding methods based on mixtures of normal distributions. Our model is supported with experimental tests that are conducted with extracted images from DIBCO 2009 and H-DIBCO 2010 benchmarks. We also report results for all four DIBCO benchmarks.
Year
DOI
Venue
2014
10.1007/s10032-013-0212-5
International Journal on Document Analysis and Recognition
Keywords
Field
DocType
historical documents,normal,binarization,handwritten,dibco,thresholding
Histogram,Computer vision,Normal distribution,Pattern recognition,Computer science,Artificial intelligence,Pixel,Thresholding,Smoothness,Log-normal distribution
Journal
Volume
Issue
ISSN
17
2
1433-2825
Citations 
PageRank 
References 
3
0.37
54
Authors
6
Name
Order
Citations
PageRank
Marte A. Ramírez-Ortegón1956.16
Lilia L Ramírez-Ramírez2322.17
Ines Ben Messaoud3596.58
Volker Märgner429529.02
Erik Cuevas5513.92
Raúl Rojas618922.57