1. Day’s Schedule 9:30-10:30: Digitization Basics 10:45-12:00: Workflow & Color Management 12:00-1:00:Lunch Break 1:00-2:00:Workflow Demo 2:15-3:30:Photoshop Tools

2. Putting Theory into Practice: Scanning Made Simple Danielle Mericle, dkm26@cornell.edu dkm26@cornell.edu

3. Part I: Digitization Overview

4. Why Digitize? Access –Fragile materials –Remove geographic barriers 24 hours day/global reach Awareness –Unique holdings now broadly available –Unlimited audience

5. Selection Criteria Copyright Content –Virtual collections building –Critical mass –Support learning and teaching –Space savings Access –Increased accessibility –New forms of use Preservation –Reduce wear and tear –Reformatting tool

6. Preparation Conservation Disbinding Tagging Organizing physical volumes, slides, etc. Safe handling and storage directions Metadata analysis

7. Digitization Decision-making factors –Resolution / PPI-DPI –Bit-depth –Threshold –Dynamic range / Histogram –Image Mode/ Color Space –File Formats –Compression Techniques –Filenaming

8. Terminology & Key Concepts Digital Images are electronic snapshots taken of a scene or scanned from documents, such as photographs, manuscripts, printed texts, and artwork. The digital image is sampled and mapped as a grid of dots or picture elements (pixels). Pixel Values: As shown in this bitonal image, each pixel is assigned a tonal value, 0 for black and 1 for white. Source: Moving Theory into Practice: Digital Imaging Tutorial

9. Terminology & Key Concepts Resolution: Ability to distinguish fine spatial detail dots-per- inch (dpi) or pixels-per-inch (ppi) are common and synonymous terms used to express resolution for digital images. The more pixels per inch, the greater the resolution. Pixel Dimensions are the horizontal and vertical measurements of an image expressed in pixels. The pixel dimensions may be determined by multiplying both the width and the height by the dpi. Source: Moving Theory into Practice: Digital Imaging Tutorial

10. 300 PPI / 600 x 600 pixel dimension 2 inches 72 PPI / 144 x 144 pixel dimension 30 PPI / 60 x 60 pixel dimension Images at Different Resolutions

11. Characters Scanned at Different Resolutions

12. Terminology & Key Concepts Bit Depth is determined by the number of bits used to define each pixel. The greater the bit depth, the greater the number of tones (grayscale or color) that can be represented. For example, an image with a bit depth of 1 has pixels with two possible values: black and white. An image with a bit depth of 8 has 2 8, or 256, possible values. Grayscale mode images with a bit depth of 8 have 256 possible gray values. RGB images are made of three color channels. An 8 bit per pixel RGB image has 256 possible values for each channel which means it has over 16 million possible color values. RGB images with 8 bits per channel (bpc) are sometimes called 24 bit images (8 bits x 3 channels = 24 bits of data for each pixel). Bitonal 1 bit Grayscale 2-8 bit (4 to 256 different shades/tones) Color24 bit (8 bits per channel)

13. Bit Depth 24 bit image / 8 bits per RGB channel (16 million possible values) 8 bit image (256 possible gray values) 1 bit image (2 possible values)

14. Threshold When scanning bitmapped images, threshold adjusts brightness & contrast of an image; density

15. Effects of Threshold` threshold = 100 threshold = 60

16. Dynamic Range & Histograms Dynamic Range is the range of tonal difference between the lightest light and darkest dark of an image. The higher the dynamic range, the more potential shades can be represented. Histograms give a quick picture of the tonal range of the image, or the image key type. A low-key image has detail concentrated in the shadows; a high-key image has detail concentrated in the highlights; and an average-key image has detail concentrated in the midtones. An image with full tonal range has a number of pixels in all areas. Identifying the tonal range helps determine appropriate tonal corrections.

17. A histogram also illustrates how pixels in an image are distributed by graphing the number of pixels at each color intensity level. The histogram shows whether the image contains enough detail in the shadows (shown in the left part of the histogram), midtones (shown in the middle), and highlights (shown in the right part) to make a good correction. Source: Adobe Help Histograms

18. Color Modes A color model describes the colors we see and work with in digital images. Each color model, such as RGB or CMYK, represents a different method (usually numeric) for describing color. A color space is a variant of a color model and has a specific gamut (range) of colors. For example, within the RGB color model are a number of color spaces: Adobe RGB, sRGB, ProPhoto RGB, and so on.

19. Color Spaces & Gamuts Human eye can recognize wide range of color Monitors can display a limited range of colors Adobe RGB common in graphics applications S-RGB common on internet & represents what most ink-jet printers can produce

20. File Formats Master Files – TIFF standard / JP2 (can have lossless compression, such as LZW) Access images - GIF and JPEG files are the most common (lossy compression) Table: Common Image File Formats http://www.library.cornell.edu/preservation/tutorial/presentation/table7- 1.html http://www.library.cornell.edu/preservation/tutorial/presentation/table7- 1.html

21. File Names Meaningful / ProsMeaningful/ConsNon-meaningful / ProsNon-meaningful / Cons Easily Identifiable, esp. if separated from original collection Long and inconsistent filenames Doesn’t sort easily If based on location or call #, risk of those identifiers changing over time Sorts easily Not tied to a physical location Hard to identify, should it get separated from original collection Requires database or tracking method (although this is generally recommended/require d regardless) Recommend: A hybrid approach- for example, sequentially derived value combined with three-letter prefix identifying collection (ex: ORN_0001.tif)

22. Methodology Digitization –One size does not fit all! –Flatbed, sheet-feed, digital camera, bound- volume, microfilm, slide, etc. Image quality –Image enhancement & color management –Archival vs. access –Immediate needs vs. future considerations

23. Translating Analog to Digital Step 1: Know your document –Identify document’s key informational content –Characterize and measure document attributes: detail, tone, color, other –Consider other variables: lighting, variations in media

24. Important Document Attributes Physical type, size, and presentation Physical condition and testimony Document type Medium and support Tone Reproduction Color Reproduction Detail

25. Translating Analog to Digital Step 2: Know your needs –Determine quality/performance objectives –Consider both immediate and long-term requirements –Balance competing factors: $, technology, users, protection of originals

26. Translating Analog to Digital Step 3: Determine digital equivalencies and corresponding quality metrics –detail size  resolution  tonal range  bit depth –Utilize representative test targets (Macbeth Color Chart or Kodak grayscale target)

27. Physical Type, Size, and Presentation Use of original or intermediate Bound vs. single leaf Physical dimensions

28. Physical Condition Potential harm to originals –Mechanical stress Strain on bindings, brittle paper, glass plates –Light and heat damage Light sensitivity, chemical instability –Competition between physical safety and good image quality

29. Protecting the Originals Require on-site imaging and training Use protective cradles and cool lights Couple treatment and scanning Sacrifice image quality

30. Physical Condition Effect on conversion requirements –Darkening pages, fading ink, burn- though, uneven printing, bleed-through, staining, foxing, buckling –Requires grayscale or color –Increases cost and file size

31. Bitonal vs. Grayscale Capture of Stained Manuscript Bitonal scanGrayscale scan

32. Document Classifications A. Printed text B. Manuscript C. Halftone D. Continuous tone E. Mixed

33. Printed Text Machine produced, hard- edge representation Digitization Challenges: –using sufficient resolution –capturing oversized documents with fine detail –handling documents that are uneven, inconsistent, low density, varied tones, or mixed sizes

34. Characters Scanned at Different Resolutions

35. Defining Detail in Text Some printed text requires tonal capture –Pages badly stained –Pages exhibit low contrast between text and background –Fine features not fully resolved –Pages contain complex graphics or important contextual information

36. Manuscripts Hand produced, soft-edge representation Digitization challenges: –determining informational content –capturing an array of media (ink, pencil) –lack of document consistency slows production

37. Halftones Regularly spaced pattern of dots or lines

38. Halftones Digitization Challenges: –Overlapping grids –Requires additional image processing or greater resolution/bit depth –Moiré can result at point of capture and at point of presentation

39. Continuous Tones Smoothly varying shades Digitization challenges: –reducing random, continuous information to samples –representing color, detail, and dynamic range –balancing capture requirements against file size

40. Mixed Documents Representing more than one category Digitization challenges: –complexity of information increases conversion or enhancement requirements –narrows range of equipment choices –increases scanning costs/times

41. Post-digitization Quality control –Determine scope and methods –Procedures and tools Image processing –Derivative creation Static or multi-resolution formats On-the-fly conversion Onscreen image quality

42. Quality Control Key factors in image quality assessment: –resolution –color and tone –overall appearance For further discussion of image quality metrics, see RLG DigiNews technical feature: http://www.rlg.org/preserv/diginews/diginews4- 4.html#technical1 Procedures –Consistent approach –Defined scope and methodology –Control QC environment

43. Recap: Aligning Document Attributes with Digital Requirements Identify key document attributes –Tone, color, and detail Characterize them, if possible through objective measurements Determine quality requirements and tolerance levels Translate between analog and digital and between scanning requirements and scanning performance

44. Part II: Workflow & Color Management

45. Digitization Workflow Prepare Material Determine & Document Benchmarks Assign Device Profile Calibrate/ Characterize Devices Scan Determine Filenames Convert to Working Space Apply Photoshop Adj Archive Derivatives Quality Control 1 Archive Masters & CM target Quality Control 2

46. Establishing the workflow Benchmarks / Scanner Settings Filenames Color management Characterize scanners Calibrate monitors Photoshop Assign device profile/ Convert to working space Image adjustment (levels, curves) Image repair (clone tool, selection, layers) Batch processing

47. Determine Imaging Benchmarks –Resolution / PPI-DPI –Bit-depth –Color Space (master vs. derivative) –File Formats (master vs. derivative) –Compression Techniques (if any) –Filenaming And Scanner Settings… –Document type –Exposure (auto exposure or no?) –Quality –Color management (on or off?)

48. DON’T FORGET TO DOCUMENT YOUR DECISIONS!!

49. What is color management, anyway? In digital imaging systems, color management is the controlled conversion between the color representations of various devices, such as scanners, digital cameras, monitors, and computer printers.

50. Color management terms* Calibrate: The process of adjusting a device to known color conditions. Commonly done with devices that change color frequently, such as monitors (phosphors lose brightness over time) and printers (proofers and other digital printing devices can change output when colorant or paper stock is changed). Characterize- Measurement of device in relation to standard color target. This process creates a profile that describes the unique color conditions found on a particular device. ICC Device Profile- A file that describes how a particular device (e.g., monitor, scanner, printer, or proofer) reproduces color (i.e., its specific color space). Profiles can be either generic or custom. *From Adobe Solutions Tech Note

51. Color Targets MacBeth - best for manuscript material and silver gelatin printsMacBeth Kodak Q13 - ideal when not utilizing color management systemKodak Q13 Kodak IT8 - best for contemporary photographs (color glossy paper)Kodak IT8 Software –InCamera software for profiling scannersInCamera –Color Eyes Display Pro Calibration deviceColor Eyes Display Pro

52. Creating a scanner profile You will need the following: –Color target –Installed Color Calibration Software, preferably InCamera Plug- In for Photoshop Scan Target in Photoshop –Clean Scanner glass –Turn off all automated color adjustment –Place chart face down, handling only the edges –Crop to edge of target –Scan at high-resolution (600 dpi) –Save as Targetname_date (macbeth_11_22_09.tif)

53. Creating a scanner profile, cont. Create the profile –Open scanned target in Photoshop –Clean image, removing any dust, etc –Open InCamera in Photoshop : Filter/Picto/InCamera4.5 –Adjust as necessary to fit squares in the middle of color patches. –Click Ok –Save file as Device_MB_Date.icc Using the profile –Scan without any auto color adjustment –Archive Master file with profile & target scan –Assign profile & convert to working space for derivative images (See scanning manual for more information)

54. Photoshop Tools Tools to use: –Levels & Curves (especially curves) –Clone Stamp –Unsharp mask –Profile assignment/conversion –Batch Processing Tools to avoid: –Automated levels –Brightness/contrast –Sharpening

55. Sample Workflow for Preservation Master Turn off automated exposure, automated color, etc Capture “raw” file Can either capture with a kodak color chart or archive with profile & macbeth target Check white/gray/black values for consistency across channels (if scanning RGB) and tonal range Archive raw file; make adjustments in PS; archive adjusted file as well.

56. Additional Resources Collaborative Digitization Program: Digital Toolbox - http://www.cdpheritage.org/digital/inde x.cfm http://www.cdpheritage.org/digital/inde x.cfm Research Libraries Group: Guides & Tools - http://www.rlg.org/en/page.php?Page_ ID=555 http://www.rlg.org/en/page.php?Page_ ID=555 IMAGELIB –To subscribe, send the message "SUB imagelib Your Full Name" to listserv@listserv.arizona.edu, or visit http://listserv.arizona.edu/cgi- bin/wa?SUBED1=imagelib&A=1 http://listserv.arizona.edu/cgi- bin/wa?SUBED1=imagelib&A=1

57. Contact Information Danielle Mericle Digital Lab Coordinator Digital Consulting and Production Services Cornell University Library dkm26@cornell.edu http://dcaps.library.cornell.edu