Handwritten text line segmentation by spectral clustering

Xuecheng Han; Hui Yao; Guoqiang Zhong

doi:10.1117/12.2266982

8 February 2017 Handwritten text line segmentation by spectral clustering

Xuecheng Han, Hui Yao, Guoqiang Zhong

Proceedings Volume 10225, Eighth International Conference on Graphic and Image Processing (ICGIP 2016); 102251A (2017) https://doi.org/10.1117/12.2266982
Event: Eighth International Conference on Graphic and Image Processing, 2016, Tokyo, Japan

Abstract

Since handwritten text lines are generally skewed and not obviously separated, text line segmentation of handwritten document images is still a challenging problem. In this paper, we propose a novel text line segmentation algorithm based on the spectral clustering. Given a handwritten document image, we convert it to a binary image first, and then compute the adjacent matrix of the pixel points. We apply spectral clustering on this similarity metric and use the orthogonal kmeans clustering algorithm to group the text lines. Experiments on Chinese handwritten documents database (HIT-MW) demonstrate the effectiveness of the proposed method.

Citation Download Citation

Xuecheng Han, Hui Yao, and Guoqiang Zhong "Handwritten text line segmentation by spectral clustering", Proc. SPIE 10225, Eighth International Conference on Graphic and Image Processing (ICGIP 2016), 102251A (8 February 2017); https://doi.org/10.1117/12.2266982

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