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

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

Putting Theory into Practice: Scanning Made Simple

Danielle Mericle, [email protected]

mailto:[email protected]

Part I: Digitization Overview

Why Digitize?

• Access – Fragile materials– Remove geographic barriers

• 24 hours day/global reach

• Awareness– Unique holdings now broadly available– Unlimited audience

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

Preparation

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

DigitizationDecision-making factors

– Resolution / PPI-DPI– Bit-depth – Threshold– Dynamic range / Histogram– Image Mode/ Color Space– File Formats– Compression Techniques – Filenaming

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


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

300 PPI / 600 x 600 pixel dimension

2 inches



Images at Different Resolutions

Characters Scanned at Different Resolutions


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 28, 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 bitGrayscale 2-8 bit (4 to 256 different shades/tones)Color 24 bit (8 bits per channel)

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)

Threshold

When scanning bitmapped images, thresholdadjusts brightness & contrast of an image; density

Effects of Threshold`

threshold = 100

threshold = 60

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.

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

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.

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

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

File Names

Meaningful / Pros Meaningful/Cons Non-meaningful / Pros

Non-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/required regardless)

Recommend: A hybrid approach- for example, sequentially derived value combined with three-letter prefix identifying collection (ex: ORN_0001.tif)

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

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

Important Document Attributes

• Physical type, size, and presentation• Physical condition and testimony• Document type• Medium and support• Tone Reproduction• Color Reproduction• Detail


• Step 2: Know your needs

– Determine quality/performance objectives

– Consider both immediate and long-term requirements

– Balance competing factors:

• $, technology, users, protection of originals


• 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)

Physical Type, Size, and Presentation

• Use of original or intermediate• Bound vs. single leaf• Physical dimensions

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

Protecting the Originals

• Require on-site imaging and training• Use protective cradles and cool lights• Couple treatment and scanning• Sacrifice image quality

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

Bitonal vs. Grayscale Capture of Stained Manuscript

Bitonal scan Grayscale scan

Document ClassificationsA. Printed textB. ManuscriptC. HalftoneD. Continuous toneE. Mixed

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

Characters Scanned at Different Resolutions

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

Manuscripts

• Hand produced, soft-edge representation

• Digitization challenges: – determining informational

content– capturing an array of media (ink,

pencil) – lack of document consistency slows

production

Halftones

• Regularly spaced pattern of dots or lines

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

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

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

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

Quality ControlKey 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

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

Part II:Workflow & Color

Management

Digitization

Workflow

PrepareMaterial Determine

& DocumentBenchmarks

Assign Device Profile

Calibrate/Characterize

Devices

Scan

DetermineFilenames

Convert to Working

Space

ApplyPhotoshop

Adj

Archive Derivatives

Quality Control 1

Archive Masters & CM target

Quality Control 2

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

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?)

DON’T FORGET

TO DOCUMENT

YOUR DECISIONS!!

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.

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

Color Targets• MacBeth - best for manuscript

material and silver gelatin prints• Kodak Q13 - ideal when not utilizing

color management system• Kodak IT8 - best for contemporary

photographs (color glossy paper) Software

– InCamera software for profiling scanners– Color Eyes Display Pro Calibration

device

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)

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)

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

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.

Additional Resources• Collaborative Digitization Program: Digital

Toolbox - http://www.cdpheritage.org/digital/index.cfm

• Research Libraries Group: Guides & Tools - http://www.rlg.org/en/page.php?Page_ID=555

• IMAGELIB – To subscribe, send the message "SUB imagelib

Your Full Name" to [email protected], or visit http://listserv.arizona.edu/cgi-bin/wa?SUBED1=imagelib&A=1

Contact Information

Danielle MericleDigital Lab CoordinatorDigital Consulting and Production ServicesCornell University [email protected]

http://dcaps.library.cornell.edu