KFBin: Kalman Filter-Based Approach for Document Image Binarization
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Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-030-27202-9_13
Reference30 articles.
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2. Calvo-Zaragoza, J., Vigliensoni, G., Fujinaga, I.: Pixel-wise binarization of musical documents with convolutional neural networks. In: 2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA), pp. 362–365. IEEE (2017)
3. Chang, C.-I.: Discrete-time Kalman filtering for hyperspectral processing. In: Real-Time Recursive Hyperspectral Sample and Band Processing, pp. 49–71. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-45171-8_3
4. Cheriet, M., Moghaddam, R.F., Hedjam, R.: A learning framework for the optimization and automation of document binarization methods. Comput. Vis. Image Underst. 117(3), 269–280 (2013)
5. Cuevas, E.V., Zaldivar, D., Rojas, R.: Kalman filter for vision tracking (2005)
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