Abstract
How to effectively and efficiently detect texts in natural scene images is a challenging problem. This paper presents a novel text detection method using localized stroke width transform. Due to the utilization of an adaptive image binarization approach and the implementation of stroke width transform in local regions, our method markedly reduces the demand of contrast between texts and backgrounds, and becomes considerably robust against edge detection results. Experiments on the dataset of ICDAR 2013 robust reading competition demonstrate that the proposed method outperforms other state-of-the-art approaches in the application of text detection in natural scene images.
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Dong, W., Lian, Z., Tang, Y., Xiao, J. (2015). Text Detection in Natural Images Using Localized Stroke Width Transform. In: He, X., Luo, S., Tao, D., Xu, C., Yang, J., Hasan, M.A. (eds) MultiMedia Modeling. MMM 2015. Lecture Notes in Computer Science, vol 8935. Springer, Cham. https://doi.org/10.1007/978-3-319-14445-0_5
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DOI: https://doi.org/10.1007/978-3-319-14445-0_5
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-14444-3
Online ISBN: 978-3-319-14445-0
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