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Analysis of Optical Character Recognition using EasyOCR under Image Degradation
Analysis of Optical Character Recognition using EasyOCR under Image Degradation
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Analysis of Optical Character Recognition using EasyOCR under Image Degradation
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Analysis of Optical Character Recognition using EasyOCR under Image Degradation
Analysis of Optical Character Recognition using EasyOCR under Image Degradation

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Analysis of Optical Character Recognition using EasyOCR under Image Degradation
Analysis of Optical Character Recognition using EasyOCR under Image Degradation
Journal Article

Analysis of Optical Character Recognition using EasyOCR under Image Degradation

2023
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Overview
This project explores EasyOCR’s performance with Latin characters under image degradation. Variables like character-background intensity difference, Gaussian blur, and relative character size were tested. EasyOCR excels in distinguishing unique lowercase and uppercase characters but tends to favor uppercase for similar shapes like C, S, U, or Z. Results showed that high character-background intensity differences affected OCR output, with confidence scores ranging from 3 % to 80%. Higher differences caused confusion between characters like o and 0, or i and 1. Increased Gaussian blur hindered recognition but improved it for certain letters like v. Image size had a significant impact, with character detection failing as sizes decreased to 40% to 30% of the original. These findings provide insights into EasyOCR’s capabilities and limitations with Latin characters under image degradation.