OCR Apparatus Region-Specific Preprocessing for Low Certainty Text

The patent divides the image into multiple regions and calculates certainty degree for each region separately rather than for the entire image. This allows identification of specific low-certainty regions that require additional preprocessing, while maintaining high-certainty regions without unnecessary processing, thus resolving the contradiction between overall processing efficiency and local recognition accuracy.

The patent applies different preprocessing operations to different regions based on their specific certainty degrees. Low-certainty regions receive additional preprocessing (such as contrast enhancement or noise reduction), while high-certainty regions are processed normally. This localized approach improves text recognition accuracy in problematic areas without sacrificing overall processing efficiency.

The patent applies additional preprocessing only to regions where it is necessary (low-certainty regions) rather than to the entire image. By identifying and targeting only the specific regions that require improved processing, the system achieves better text recognition accuracy where needed while avoiding the time and computational overhead of processing the entire image with enhanced operations.

The system automatically identifies low-certainty regions and applies appropriate preprocessing operations without requiring manual intervention. The certainty degree calculation and region selection are performed autonomously by the processing system, enabling it to self-optimize the preprocessing approach for each image based on its specific characteristics.