Comments (2)
waldoj
commented on August 30, 2024
The test cases aren't great. I OCRed these files fairly naively, using PyPDFOCR (which, in turn, relies on Poppler and Tesseract), and the quality of the OCR is low, in my experience. The biggest problem is that it just randomly fails to OCR digits, digits that are perfectly obvious. So 123-45-6789 might be OCRed as 123-4-6789 and that, of course, is not identified as an SSN.
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waldoj
commented on August 30, 2024
The good news is that I was able to identify some common real-world problems in identifying SSNs (#1, #3, #4, #5), each of which is very solvable.
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Related Issues (11)
- OCR software confuses letters and numbers HOT 4
- Require either 0 or 2 hyphens HOT 4
- Deal with em dashes, en dashes, etc. HOT 2
- Require that SSNs be neither preceded nor followed by digits HOT 2
- Support spaces as SSN separators
- Modify background image to draw a black box
- Replace identified target string with equivalent-length redaction vector data
- Identify target text within PDF text HOT 1
- Save the fully redacted PDF HOT 3
- Create a test harness to evaluate effectiveness HOT 1
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