In this work, artificial neural networks are used to clean and enhance scanned images for a handwritten recognition task. Multilayer perceptrons are trained in a supervised way using a set of simulated noisy images together with the corresponding clean images for the desired output. The neural network acquires the function of a desired enhancing method. The performance of this method has been evaluated for both noisy artificial and natural images. Objective and subjective methods of evaluation have shown a superior performance of the proposed method over other conventional enhancing and cleaning filters. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Hidalgo, J. L., España, S., Castro, M. J., & Pérez, J. A. (2005). Enhancement and cleaning of handwritten data by using neural networks. In Lecture Notes in Computer Science (Vol. 3522, pp. 376–383). Springer Verlag. https://doi.org/10.1007/11492429_46
Mendeley helps you to discover research relevant for your work.