Purpose
Present OCR with a cleaner, more consistent representation of the printed text.
Role in the complete pipeline
Enhancement bridges camera variability and recognition by adjusting scale, contrast, noise, and edge clarity.
INPUT
→A perspective-corrected page or text-region crop.
METHOD
- Convert to grayscale
- Normalize local contrast
- Denoise before sharpening
- Compare restrained preprocessing variants
One or more enhanced OCR candidates with quality metadata.
Common failure cases
- Harsh thresholding erases thin strokes
- Sharpening creates false edges
- Glare has already removed information
- Low-resolution text cannot be reconstructed
How VisoraAI responds
- Keep the unmodified crop as a candidate
- Reject destructive variants
- Route persistent glare or blur to guidance
Current limitations
- No filter can restore missing pixels
- One preprocessing recipe does not fit every print style
Planned improvements
- Choose variants using measured OCR quality
- Localize glare before processing
- Profile document-specific settings