Title :
Handwritten Line Detection via an EM Algorithm
Author :
Cruz, Francisco ; Ramos Terrades, Oriol
Author_Institution :
Comput. Vision Center, Univ. Autonoma de Barcelona, Barcelona, Spain
Abstract :
In this paper we present a handwritten line segmentation method devised to work on documents composed of several paragraphs with multiple line orientations. The method is based on a variation of the EM algorithm for the estimation of a set of regression lines between the connected components that compose the image. We evaluated our method on the ICDAR2009 handwriting segmentation contest dataset with promising results that overcome most of the presented methods. In addition, we prove the usability of the presented method by performing line segmentation on the George Washington database obtaining encouraging results.
Keywords :
document image processing; expectation-maximisation algorithm; handwriting recognition; image segmentation; EM algorithm; George Washington database; ICDAR2009 handwriting segmentation contest dataset; connected components; handwritten line detection; handwritten line segmentation method; multiple line orientations; regression lines; Databases; Equations; Estimation; Gaussian distribution; Image segmentation; Mathematical model; Text analysis; Expectation-Maximization algorithm; Handwritten Line Segmentation; Linear regression;
Conference_Titel :
Document Analysis and Recognition (ICDAR), 2013 12th International Conference on
Conference_Location :
Washington, DC
DOI :
10.1109/ICDAR.2013.147