Paper
24 January 2011 A perceptive method for handwritten text segmentation
Author Affiliations +
Proceedings Volume 7874, Document Recognition and Retrieval XVIII; 78740C (2011) https://doi.org/10.1117/12.873037
Event: IS&T/SPIE Electronic Imaging, 2011, San Francisco Airport, California, United States
Abstract
This paper presents a new method to address the problem of handwritten text segmentation into text lines and words. Thus, we propose a method based on the cooperation among points of view that enables the localization of the text lines in a low resolution image, and then to associate the pixels at a higher level of resolution. Thanks to the combination of levels of vision, we can detect overlapping characters and re-segment the connected components during the analysis. Then, we propose a segmentation of lines into words based on the cooperation among digital data and symbolic knowledge. The digital data are obtained from distances inside a Delaunay graph, which gives a precise distance between connected components, at the pixel level. We introduce structural rules in order to take into account some generic knowledge about the organization of a text page. This cooperation among information gives a bigger power of expression and ensures the global coherence of the recognition. We validate this work using the metrics and the database proposed for the segmentation contest of ICDAR 2009. Thus, we show that our method obtains very interesting results, compared to the other methods of the literature. More precisely, we are able to deal with slope and curvature, overlapping text lines and varied kinds of writings, which are the main difficulties met by the other methods.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Aurélie Lemaitre, Jean Camillerapp, and Bertrand Coüasnon "A perceptive method for handwritten text segmentation", Proc. SPIE 7874, Document Recognition and Retrieval XVIII, 78740C (24 January 2011); https://doi.org/10.1117/12.873037
Lens.org Logo
CITATIONS
Cited by 14 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Image segmentation

Databases

Image resolution

Fermium

Frequency modulation

Monochromatic aberrations

Feature extraction

RELATED CONTENT


Back to Top