Abstract
With the increasing resolution and availability of digital cameras, text detection in natural scene images receives a growing attention. When taking pictures using a mobile device, people generally only concerned with interesting texts instead of all of the text in the image. In this paper, we propose an interactive method to detect and extract interesting text in natural scene images. We first draw a line to label a region which contains the texts we want to detect. Then a coarse-to-fine strategy is adopted to detect texts in this label region. For coarse detection, we apply Canny edge detection and connected component (CC)-based approach to extract coarse region from the label region. For fine detection, some heuristic rules are specially designed to eliminate some non-text CCs and then to merge the remaining CCs in the coarse region. To better evaluate our algorithm, we collect a new dataset, which includes various texts in diverse real-world scenarios. Experimental results on the proposed dataset demonstrate very promising performance on detecting text in complex natural scenes.
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Acknowledgments
This work was supported by the National Natural Science Foundation of China (NSFC) under Grants No.60933010, No.61172103 and No.61271429.
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Hu, J., Xiao, B., Wang, C., Shi, C., Gao, S. (2014). Interactive Scene Text Detection on Mobile Devices. In: Farag, A., Yang, J., Jiao, F. (eds) Proceedings of the 3rd International Conference on Multimedia Technology (ICMT 2013). Lecture Notes in Electrical Engineering, vol 278. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41407-7_28
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DOI: https://doi.org/10.1007/978-3-642-41407-7_28
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