The document discusses Optical Character Recognition (OCR) technology, which converts images of text into machine-encoded text to facilitate editing, searching, and data mining. It highlights various OCR software like ABBYY FineReader Pro, Tesseract, and Adobe Document Cloud, along with their features and usage for document processing. The document also mentions the Visual Resources Center's role in assisting graduate students with OCR technology in research projects.

1. OCR in the VRC
Equipment and Software for New Users and New Uses
VRA LA
March 26, 2019

2. What is OCR? Optical Character Recognition
Mechanical conversion an image, scanned document,
photograph, or PDF of text into machine-encoded text
that allows users to:
● Edit, search, or display text
● Text-to-speech
● Data mining & text mining

3. Why OCR? CTRL+F
Corpus building
DH research projects, especially text analysis

4. Our Context Stand-alone VRC in the Art History Department, lot of
graduate student use
Decentralized campus, but VRC collaborates with
Library, Research Computing Center, Humanities
Computing, etc.

5. ABBYY FineReader
Pro
Costs $200
Most accurate!
Import:
PDF files, photos, scans, etc
Export:
PDF, Microsoft Word, Excel, and PowerPoint, Text,
CSV, etc.
192 languages:
Roman alphabet, Cyrillic alphabet, CJK characters
Does not work well for Arabic or other script
languages such as Tamil
Teachable!

6. ABBYY - Handling of complex layouts including text, tables, and pictures

7. ABBYY - Pattern training

8. Other Software Tesseract
Free, open source
Currently supported by Google
(better for Arabic, potentially better for massive data
sets)
Adobe Document Cloud
Zeutschel and Opus Freeflow software have their own
proprietary OCR software built-in
Handwriting recognition?
Transkribus
Google Cloud Vision
(LUNA integration)

9. Imaging for OCR
Why focus on text when we’re experts
in images?
Scanning advice
Use black paper to prevent text or image bleed-
through on flatbed or overhead scanners
Use hot pink paper for spreads on black
background to help BookEye scanner find and
focus
Provide photography tips for special collections
settings
Pre-Processing Advice
● High-contrast grayscale/black-and-white
● Deskew or straighten lines of text
● Remove any dust, scratches, etc. near the
text

12. What We’ve Seen About 5-10 unique users a year
Primarily History and Sociology PhD students working
on text mining or network analysis projects
Some students just here for the CTRL+F
Set expectations of what we can reasonably provide
Group outreach vs. individual orientations
Increase in campus resources, including staff

13. The Takeaway?

14. Questions?
Bridget Madden
Associate Director, Visual Resources Center
University of Chicago Department of Art History
bridgetm@uchicago.edu
@UChicagoVRC