Title :
Template Based Segmentation of Touching Components in Handwritten Text Lines
Author :
Kang, Le ; Doermann, David
Author_Institution :
Inst. for Adv. Comput. Studies, Univ. of Maryland, College Park, MD, USA
Abstract :
In this paper, we present a template based approach to the segmentation of touching components in handwritten text lines. Local patches around touching components are identified and a dictionary is created consisting of template patches together with their correct segmentations. We use two shape context based methods to compute similarity between input patches and dictionary templates to find the best match. The template´s known segmentation is then transformed to segment the input patch. Experiments are carried on a dataset of touching text lines.
Keywords :
image segmentation; text analysis; dictionary templates; handwritten text lines; input patch segmentation; local patch; shape context based methods; template based segmentation approch; template patch; touching components; Context; Dictionaries; Handwriting recognition; Image segmentation; Shape; Testing; Training; dictionary; inner-distance; segmentation; shape context; thin-plate-spline; touching;
Conference_Titel :
Document Analysis and Recognition (ICDAR), 2011 International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4577-1350-7
Electronic_ISBN :
1520-5363
DOI :
10.1109/ICDAR.2011.120