Analyzing bulk OCR Results Among Mixed Typed and Handwritten Documents

Tommy Keswick
Caltech Library

Problems

  • Errant HTML in OCR text

HTML in Search Results

HTML in Search Results

HTML in Search Results

HTML in Search Results

Problems

  • Errant HTML in OCR text
  • Bias towards typed documents in search results

Approaches

  • analyze existing tesseract results
    • run statistics with dictionary words
    • throw out junk ocr
  • generate better ocr/htr with new tools
    • google cloud vision
    • microsoft azure computer vision

Results

  • custom analysis
    • plotted dictionary results
    • spot-checked graphs
    • decided on some thresholds
  • online services
    • early exploration
    • custom software

Script Data

Ignore Percentage

Dictionary Percentage
(of total)

Dictionary Percentage
(of non-ignored)

Thresholds

  • dictionary percentage of non-ignored
    • >55
  • dictionary percentage of total
    • >35

Online Services

Next Steps

  • better text analysis
  • rerun htr
  • convert json to hocr

Collaboration

  • tkeswick@caltech.edu
  • https://github.com/caltechlibrary/ocr-plotting
  • https://github.com/caltechlibrary/ocre
  • https://github.com/caltechlibrary/handprint

Analyzing bulk OCR Results Among Mixed Typed and Handwritten Documents

By t4k

Analyzing bulk OCR Results Among Mixed Typed and Handwritten Documents

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