Orientation Robust Text Line Detection in Natural Images

Le Kang, Yi Li, David Doermann
2014 2014 IEEE Conference on Computer Vision and Pattern Recognition  
In this paper, higher-order correlation clustering (HOCC) is used for text line detection in natural images. We treat text line detection as a graph partitioning problem, where each vertex is represented by a Maximally Stable Extremal Region (MSER). First, weak hypotheses are proposed by coarsely grouping MSERs based on their spatial alignment and appearance consistency. Then, higherorder correlation clustering (HOCC) is used to partition the MSERs into text line candidates, using the
more » ... as soft constraints to enforce long range interactions. We further propose a regularization method to solve the Semidefinite Programming problem in the inference. Finally we use a simple texton-based texture classifier to filter out the non-text areas. This framework allows us to naturally handle multiple orientations, languages and fonts. Experiments show that our approach achieves competitive performance compared to the state of the art.
doi:10.1109/cvpr.2014.514 dblp:conf/cvpr/KangLD14 fatcat:jeqnmviizngmdkpa5zyfwj7sdy