Text Line Segmentation in Handwritten Document Images Using Tensor Voting

Toan Dinh NGUYEN  Gueesang LEE  

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E94-A   No.11   pp.2434-2441
Publication Date: 2011/11/01
Online ISSN: 1745-1337
DOI: 10.1587/transfun.E94.A.2434
Print ISSN: 0916-8508
Type of Manuscript: PAPER
Category: Image
text line segmentation,  tensor voting,  text string,  handwritten document image,  

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A novel grouping approach to segment text lines from handwritten documents is presented. In this text line segmentation algorithm, for each text line, a text string that connects the center points of the characters in this text line is built. The text lines are then segmented using the resulting text strings. Since the characters of the same text line are situated close together and aligned on a smooth curve, 2D tensor voting is used to reduce the conflicts when building these text strings. First, the text lines are represented by separate connected components. The center points of these connected components are then encoded by second order tensors. Finally, a voting process is applied to extract the curve saliency values and normal vectors, which are used to remove outliers and build the text strings. The experimental results obtained from the test dataset of the ICDAR 2009 Handwriting Segmentation Contest show that the proposed method generates high detection rate and recognition accuracy.