An objective method to evaluate stroke-width measures for binarized documents

In this article, we propose an objective method to evaluate stroke-width measures. With this aim, we discuss the relevance of features based on the stroke width for document analysis. Then, we point out that most of the consulted references have a vague definition of stroke width. Because of this, we propose a formal definition of the stroke-width and remark the linearity of the stroke-width as an important property. Inspired by these ideas, we propose a measure together with a dataset to evaluate the linearity of the measurements of the stroke width and conduct an evaluation for seven well-known stroke-width methods. Our experiments have interesting results, like the fact that the most popular method is the one with the worst performance and that the best method is the easiest to implement. We hope that our objective evaluation assists further authors to choose suitable stroke-width methods for their applications. Zapotitlán 2013 IEEE

An optimization for binarization methods by removing binary artifacts

In this article, we introduce a novel technique to remove binary artifacts. Given a gray-intensity image and its corresponding binary image, our method detects and remove connected components that are more likely to be background pixels. With this aim, our method constructs an auxiliary image by the minimum-error-rate threshold and, then, computes the ratio of intersection between the connected components of the original binary image and the connected components of the auxiliary image. Connected components with high ratio are considered true connected components while the rest are removed from the output. We tested our method in binarization methods for historical documents (handwritten and printed). Our results are favorable and indicate that our method can improve the outputs from diverse binarization methods. In particular, a high improvement was observed for printed documents. Our method is easy to implement, has a moderate computational cost, and has two parameters whose model interpretation allows an easy empirical selection. © 2013 Elsevier B.V. All rights reserved

A model for the gray-intensity distribution of historical handwritten documents and its application for binarization

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describe mathematically and experimentally the gray-intensity distributions of the fore- and background of handwritten historical documents.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. � 2013 Springer-Verlag Berlin Heidelberg

An analysis of the transition proportion for binarization in handwritten historical documents

In this paper, we will present a mathematical analysis of the transition proportion for the normal threshold (NorT) based on the transition method. The transition proportion is a parameter of NorT which plays an important role in the theoretical development of NorT. We will study the mathematical forms of the quadratic equation from which NorT is computed. Through this analysis, we will describe how the transition proportion affects NorT. Then, we will prove that NorT is robust to inaccurate estimations of the transition proportion. Furthermore, our analysis extends to thresholding methods that rely on Bayes rule, and it also gives the mathematical bases for potential applications of the transition proportion as a feature to estimate stroke width and detect regions of interest. In the majority of our experiments, we used a database composed of small images that were extracted from DIBCO 2009 and H-DIBCO 2010 benchmarks. However, we also report evaluations using the original (H-)DIBCO's benchmarks. © 2014 Elsevier Ltd