@conference {19319,
	title = {Learning Text-line Segmentation using Codebooks and Graph Partitioning},
	booktitle = {International Conference on Frontiers in Handwriting Recognition (ICFHR)},
	year = {2012},
	pages = {63-68},
	abstract = {In this paper, we present a codebook based method for handwritten text-line segmentation which uses image patches in the training data to learn a graph-based similarity for clustering. We first construct a codebook of image-patches using K-medoids, and obtain exemplars which encode local evidence. We then obtain the corresponding codewords for all patches extracted from a given image and construct a similarity graph using the learned evidence and partitioned to obtain textlines. Our learning based approach performs well on a field dataset containing degraded and un-constrained handwritten Arabic document images. Results on ICDAR 2009 segmentation contest dataset show that the method is competitive with previous approaches.},
	author = {Kang,Le and Kumar,Jayant and Ye,Peng and David Doermann}
}
