Localization of characters horizontal bounds in text line images with fully convolutional network

Yulia S. Chernyshova; Anastasiya N. Chirvonaya; Alexander V. Sheshkus

doi:10.1117/12.2559449

31 January 2020 Localization of characters horizontal bounds in text line images with fully convolutional network

Yulia S. Chernyshova, Anastasiya N. Chirvonaya, Alexander V. Sheshkus

Proceedings Volume 11433, Twelfth International Conference on Machine Vision (ICMV 2019); 114333F (2020) https://doi.org/10.1117/12.2559449
Event: Twelfth International Conference on Machine Vision, 2019, Amsterdam, Netherlands

Abstract

Character segmentation is one of the crucial problems of modern text line recognition methods. In this paper, we propose a per-character segmentation method based on the light weight convolutional neural network (CNN) which is suitable for on-premise applications for various mobile devices. The distinctive feature of our method is that it provides the coordinates of the start and end points of each character, not the coordinates of the “cut” between two characters. It allows us to utilize known geometrical properties of glyphs efficiently. Consequently, the target character images are not flawed because of characters intersections or wide spaces. We present the results measured for text lines with various letter spacing. Results illustrate that the proposed method decreases the segmentation error rate for the majority of test datasets.

Citation Download Citation

Yulia S. Chernyshova, Anastasiya N. Chirvonaya, and Alexander V. Sheshkus "Localization of characters horizontal bounds in text line images with fully convolutional network", Proc. SPIE 11433, Twelfth International Conference on Machine Vision (ICMV 2019), 114333F (31 January 2020); https://doi.org/10.1117/12.2559449

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