Reference for citation: Tatarnikova T. M., Shihotov A. A. Methods of preprocessing of digitized handwritten documents. Journal of Instrument Engineering. 2025. Vol. 68, N 6. P. 494–499 (in Russian). DOI: 10.17586/0021-3454-2025-68-6-494-499.

Abstract. The problem of automating the analysis of handwritten documents is solved. It is shown that artificial neural networks capable of recognizing images after training on the original data set are used to solve such problems. At the same time, the quality of recognizing new images largely depends on the stage of pre-processing of digitized handwritten documents. A particular preprocessing problem is considered - removing cell lines from an image of a notebook sheet. Four methods of image filtering are analyzed using the OpenCV library of the Python language. A neural network of convolutional architecture is trained to recognize handwritten characters. The work of the trained neural network on documents preprocessed by different algorithms is demonstrated.

Keywords: image recognition, handwritten document, neural networks, noise, preprocessing, recognition quality

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