整理现实场景干扰因素，提升OCR实际使用效果
Guidelines for External Disturbance Factors in the Use of OCR in Real-World Environments
- 梳理真实环境中影响OCR的外部干扰因素及其导致的图像退化
- 构建干扰因素与图像质量问题的对应关系表
- 提供实用指南，帮助用户规避干扰、提升识别准确率
随着人工智能技术的发展，OCR性能不断提升。然而，随着应用场景的扩展，各类使用环境带来的干扰因素增多，导致其难以发挥应有的性能，造成特定条件下识别准确率下降，增加了识别设备的质量控制难度。为确保用户能正确使用OCR，本文系统整理了真实世界中引起性能下降的外部干扰因素及其引发的图像退化现象，构建了外部干扰因素表，并说明如何有效利用该表，形成可操作的使用指南。
原文摘要 · Abstract (English)
The performance of OCR has improved with the evolution of AI technology. As OCR continues to broaden its range of applications, the increased likelihood of interference introduced by various usage environments can prevent it from achieving its inherent performance. This results in reduced recognition accuracy under certain conditions, and makes the quality control of recognition devices more challenging. Therefore, to ensure that users can properly utilize OCR, we compiled the real-world external disturbance factors that cause performance degradation, along with the resulting image degradation phenomena, into an external disturbance factor table and, by also indicating how to make use of it, organized them into guidelines.
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