targets as tools, not talismans - don williams

Image Science Associates

ZA – October, 2013

Targets as Tools

Don Williams - Image Science Associates -

[email protected]

Not Talismans

If you aim at nothing, you’ll hit it every time



What makes cultural heritage imaging different ?

-  Future Re-purposing

-  Variety of use cases

-  Information durability

-  Information critical

-  Images, not pictures

-  Scientific and

research component

- High volume, High speed

- Think manufacturing

- Think error management



Targets Physical references for measuring and

monitoring imaging performance

a requirement for disposable dog biscuit packages



Target Examples

• Intended for both calibration, performance testing, and quality control.

• Act as an archeological reference for light and resolution values. Required for change detection.

• Things to consider:

- Do they suit your purpose ?

- How comprehensive are they ?

- Are they self described ?

- Reflection or Transmission



Why Use Targets ?

•  Quality control and industry compliance

•  Consistent product

•  Verify vendor’s claims

•  Managing expectations – acceptance testing

•  Accurate Metadata population

•  Diagnostics – problem solving and image processing identification. Less rework

•  Effective communication

•  Corrective actions

Used by both US and Netherlands Initiatives



The Top Ten FourTips

1 – Targets as Tools, Not Talismans

2 – Get the exposure correct

3 – Keep the Neutrals neutral

4 – Don’t confuse Pixels with Resolution

5 –

6 –

7 –

8 –

9 –

10 –



What You’ll see

•  Standardized ways to measure scanner/camera performance

•  Identify sources of variability in digital imaging

•  Introduce imaging quality control procedures into workflows.

•  Use easy, non-disruptive ways to monitor performance



What is an image ? ….and how is it measured ?

- A two dimensional spatial structure of varying light levels. It is characterized by measuring a camera or

scanner’s response to light levels over a two

dimensional space. These levels are often classified into colors types ( i.e. RGB)

- Changes in light can occur over short distances, like

edges,( high frequencies) or larger distances or areas,

like sky or facial features( low frequencies).

Targets act as known input references by which

a camera/scanner’s output can be compared.

SPACE & LIGHT



Digital Image Capture System - From light to numbers -

The different ways an image is modified at capture

Digital image file

light source

Image forming optics

sensor sample Processing

1. Introduction



Targets For Benchmarking

light source



Digital image file

Targets and Performance Analysis Software



How Targets Are Used to Measure and Manage Image Quality

•  Accuracy - Image values from a target are compared with established aim values. These values are typically use-case dependent.

•  Precision - Tolerances around these aims are also provided. Small tolerances

imply greater precision but also higher production costs. The opposite is true for

large tolerances.

Consistent performance is often more important than accuracy.

variation

bias



- Targets – Good measurements require good targets

Target Elements 1)  ISO Frequency Response (SFR) and resolution

over the field of view. (7” x 10”)

2)  Human interpretable resolution features

3)  Dimensional scales for sampling confirmation

4)  Automated feature detection

5)  Neutral gray uniform background

6)  Ten spectrally neutral gray patches

7)  Self described colorimetric patch annotations

Device Target Object Target



Important Image Quality metrics to monitor

•  Grayscale response

•  White Balance /Color •  Resolution



Correct Exposure via OECF ( tone transfer)

Density

OECF example

0

50

100

150

200

250

0 0.5 1 1.5 2 neutral (gray) density

aver

age

gree

n co

unt v

alue

( 8

bit)



White Balance - Keep all of the neutrals, neutral -

OECFs can be measured for each color channel using a target’s neutral gray patches.

85% of good color imaging performance is keeping the Red, Green, and Blue OECFs the same… Really!

This is a good example of a well white balanced capture

Note that all color channel OECFs lie on top of each other



White Balance

This is an example where the white balance performance is marginal.

Note how the blue channel OECF departs from the red and green OECF



White Balance Assessment Photoshop Histograms

Though gray patches appear gray, the one patch is actually slightly colored.

All three histogram should align if white balance is correct



Resolution Example

Dpi scale

1 line = 1 space = 1/200“

1 line = 1 space = 1/300“

1 line = 1 space = 1/400“

Etc.



# Pixel quantity is not image resolution: quantity vs. quality

Limiting resolution = whenever all five lines are undetectable

Though the sampling rate is increased to 600 dpi the true resolution for this scanner is only 300 dpi.

Resolution

Sampling Frequency



Performance Monitoring

What could go wrong ?



What’s missing from this picture ?

The performance of a digital capture system at the sensor and beyond is influenced by all of the above in

addition to operator training and environment.

The different ways an image is modified at capture

Digital image file

light source



1. Introduction



Session-to-Session Performance Using Device Target



Workflow Performance Monitoring

Book Scanner Example



Workflow Performance Monitoring

Book scanner example

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- Workflow Performance Monitoring keeping it simple with gray scales

Book Scanner Example



- Workflow Performance Monitoring – OECF four-day holiday syndrome



How to Start

•  Identify a small pilot project –  Equipment Benchmarking ? –  Workflow Monitoring ?

•  Choose an appropriate target –  Device target –  Object target

•  Practice introducing targets –  Will it remain in place ? –  Technique, not results –  How often ?

•  Don’t do too much –  Do not analyze data –  Small amounts of data

•  Collect data



End

1907 autochrome

targets as tools, not talismans - don williams

Technology

image science associatesthe

space light za

targets neutral gray

white balance performance

good color imaging performance

neutral oecfs

time za

neutral gray densitydensityza