Symmetry-Based Text Line Detection in Natural Scenes

Zheng Zhang, Wei Shen, Cong Yao, Xiang Bai; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015, pp. 2558-2567

Abstract


Recently, a variety of real-world applications have triggered huge demand for techniques that can extract textual information from natural scenes. Therefore, scene text detection and recognition have become active research topics in computer vision. In this work, we investigate the problem of scene text detection from an alternative perspective and propose a novel algorithm for it. Different from traditional methods, which mainly make use of the properties of single characters or strokes, the proposed algorithm exploits the symmetry property of character groups and allows for direct extraction of text lines from natural images. The experiments on the latest ICDAR benchmarks demonstrate that the proposed algorithm achieves state-of-the-art performance. Moreover, compared to conventional approaches, the proposed algorithm shows stronger adaptability to texts in challenging scenarios.

Related Material


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[bibtex]
@InProceedings{Zhang_2015_CVPR,
author = {Zhang, Zheng and Shen, Wei and Yao, Cong and Bai, Xiang},
title = {Symmetry-Based Text Line Detection in Natural Scenes},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2015}
}