Guidelines for External Disturbance Factors in the Use of OCR in Real-World Environments

TL;DR

Addressing OCR degradation from real-world disturbances, the paper builds a comprehensive external-disturbance factor table and associated guidelines. It defines non-uniform illumination levels and OCR grades, and catalogs illumination, obstacles, objects, camera/photographer, and scene factors with mappings to degradation phenomena. It then presents practical utilization methods: data augmentation, and reconfirmation workflows for users, to diagnose and mitigate issues. The resulting framework enables systematic quality control and more reliable OCR deployment in real-world environments.

Abstract

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.

Figures (14)

• Figure 1: Examples of Character and Background Pixels
• Figure 2: Example of a One-Character Region
• Figure 3: Example of a Document or Form Image with Level I Non-uniform Illumination
• Figure 4: Example of a Histogram for a Document or Form Image with Level I Non-uniform Illumination
• Figure 5: Example of a Document or Form Image with Level II Non-uniform Illumination