Abstract
We present modifications in a local operator known as stroke width transform (SWT) in order to improve its performance to detect Race Bib Numbers (RBNs) from natural images of running competitions. The original SWT algorithm is a simple and yet one of the top competitive algorithms for text detection. The proposal adds a Hue channel similarity test in the neighborhoods of edge borders candidates, and it limits the length of the stroke according to aimed characters at the images. We tested the proposed, and the original approach, using a publicly available database of 217 images in different conditions. The suggested approach outperformed the original one, both in sizes of width maps, and on RBNs detection. This research is not an end-to-end RBNs recognition system, so we focused on the improvements of the SWT algorithm in order to provide a more efficient method for future use in automated systems.
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de Jesus, W.M., Borges, D.L. (2018). An Improved Stroke Width Transform to Detect Race Bib Numbers. In: Martínez-Trinidad, J., Carrasco-Ochoa, J., Olvera-López, J., Sarkar, S. (eds) Pattern Recognition. MCPR 2018. Lecture Notes in Computer Science(), vol 10880. Springer, Cham. https://doi.org/10.1007/978-3-319-92198-3_27
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DOI: https://doi.org/10.1007/978-3-319-92198-3_27
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