Scene text detection based on pruning strategy of MSER-trees and Linkage-trees
Jin Ma, Weiqiang Wang, Ke Lü, Jianshe Zhou · 2017
The extraction and recognition of scene text in images is an important way to understand the semantic information in image. By now, scene text detection is still a challenging problem. In this paper, we present a scene text localization method based on the pruning of Maximally Stable Extremal Region (MSER) tree and Linkage-tree. Concretely, the MSER-tree is first constructed and overlap MSERs are removed by the nonmaximum suppression strategy. Further, the linkage-trees are constructed and pruned based on the features considering the nodes themselves and their siblings. Finally, the non-text lines are eliminated based on to the CNN-based features and intensity contrast. Experimental results on two challenging datasets demonstrate the effectiveness of the proposed method.