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Abstract
This article provides a comprehensive analysis of the impact of interpolation-based image restoration approaches on the performance of optical character recognition (OCR) systems. The study comparatively examines bilinear, bicubic, spline, Lanczos, and adaptive interpolation methods, and evaluates their results using image quality metrics and OCR accuracy indicators. The obtained results demonstrate that preserving the structural integrity of images significantly improves the accuracy of OCR systems. At the same time, the balance between computational efficiency and accuracy is identified as a key factor.
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