1. Assessing color reproduction tolerances in commercial
print workflow
G. Beretta1 E. Hoarau1 S. Kothari1 I-J. Lin2 J. Zeng1
1 Hewlett-Packard Laboratories, 1501 Page Mill Rd., Palo Alto, California
2 MulticoreWare Inc., 1375 S. DeAnza Blvd., Cupertino, California
Color Imaging XVII:
Displaying, Processing, Hardcopy, and Applications
San Francisco Airport, 24 – 26 January 2012
Giordano Beretta (HP Labs) Color Imaging XVII EI 2012 paper 8292-32 1 / 12

2. The nightmare of ICC profiles
the ICC profile standard has no provisions for workflow
oftentimes embedded profiles are incorrect
oftentimes profiles are of poor quality
workflow system must be able to swap out profiles
want to target good enough quality for given price point (SLA)
select relevant papers:
Lammens, “Night of the living color: horror scenarios in color
management land,” this conference 1998
Phillips et al., “Comparing image quality of print-on-demand books and
photobooks from web-based vendors,” JEI 2010
Beretta et al., “ICC profiles: are we better off without them?” this
conference 2011
Falkenstern et al., “Adaptively selecting a printer color workflow,” NIP
2011
Giordano Beretta (HP Labs) Color Imaging XVII EI 2012 paper 8292-32 2 / 12

3. Assessing print quality
average ∆E values are not useful
a useful metric must allow specific assessment
Peter Zolliker et al. from EMPA have proposed several more useful
methods
is there a simpler method?
Giordano Beretta (HP Labs) Color Imaging XVII EI 2012 paper 8292-32 3 / 12

4. Color fidelity vs. color integrity
in practice, color fidelity is not that critical
Phillips et al., “Comparing image quality of print-on-demand books and
photobooks from web-based vendors,” JEI 2010
print does not contain sets of unrelated colors but color palettes
goal: preserve the integrity of color palettes
Example (catalog selling denim garments)
One page might have jeans in original, washed, and stone-washed denim,
while a second page might have corresponding jackets. The specific hue of
each garment is less important than being able to match jackets to jeans while
preserving the rank of the processes
Giordano Beretta (HP Labs) Color Imaging XVII EI 2012 paper 8292-32 4 / 12

5. Farnsworth-Munsell 100-hue test
in the case of humans, color discrimination can be assessed with the
Farnsworth-Munsell 100-hue test
can we use this test for color reproduction systems?
Giordano Beretta (HP Labs) Color Imaging XVII EI 2012 paper 8292-32 5 / 12

6. Scoring transpositions
Giordano Beretta (HP Labs) Color Imaging XVII EI 2012 paper 8292-32 6 / 12

7. Graphical evaluation
2 1 85 84 83 2 1 85 84 83
4 3 82 4 3 82
5 81 5 81
6 80 6 80
7 13 79 7 13 79
8 8
9 12 78 9 12 78
10 77 10 77
11 11
11 76 11 76
10 10
12 75 12 75
9 9
13 13
8 74 8 74
14 14
7 73 7 73
15 15
6 72 6 72
16 16
5 5
17 71 17 71
4 4
18 3 70 18 3 70
19 69 19 69
R R
20 YR RP 20 YR RP
68 68
21 21
P 67 P 67
Y Y
22 22
66 66
23 23
65 65
GY PB GY PB
24 24
64 64
25 25
G B G B
63 63
26 BG 26 BG
62 62
27 27
28 61 28 61
29 60 29 60
30 59 30 59
31 58 31 58
32 57 32 57
33 33
56 56
34 34
55 55
35 35
36 54 36 54
37 53 37 53
38 52 38 52
39 51 39 51
40 50 40 50
41 42 49 41 42 49
43 44 45 46 47 48 43 44 45 46 47 48
Giordano Beretta (HP Labs) Color Imaging XVII EI 2012 paper 8292-32 7 / 12

8. Practical application
FM-100 assesses entire hue circle
we need to assess only the critical color ranges
include one or more scales in the crop margin
normalize scores to FM-100
examples of parameters to assess:
ICC profile plausibility & correctness
ICC profile reputation & precision
rendering intent
gamut mapping algorithm
black skeleton
halftoning
inks, process vs. Hexachrome; spot colors
media
Giordano Beretta (HP Labs) Color Imaging XVII EI 2012 paper 8292-32 8 / 12

9. Example
A uniform color scale in CIELAB from (80, 15, 2) to (85, 20, 45)
86
40
84
L*
b*
82
20
80
14 16 18 20 0
14 16 18 20
a* a*
The non-uniformities are due to rounding the coordinates to one decimal digit
Giordano Beretta (HP Labs) Color Imaging XVII EI 2012 paper 8292-32 9 / 12

10. Reproduction on office laser printer
88
40
84
L*
b*
20
80
76 0
14 16 18 20 14 16 18 20
a* a*
∆E94 = 5.6
Giordano Beretta (HP Labs) Color Imaging XVII EI 2012 paper 8292-32 10 / 12

11. Comparison of 3 devices
24
84
22 40
L* device
a* device
b* device
20
80
20
18
76 16 0
76 80 84 16 18 20 22 24 0 20 40
L* a* b*
∆E94 :
green device: 5.6
red device: 1.2
blue device: 0.7
Giordano Beretta (HP Labs) Color Imaging XVII EI 2012 paper 8292-32 11 / 12

12. Physical vs. simulated
add test strip add test strip
RIP RIP
print extract color scale
measure test strip predict colorimetry
score color scale score color scale
physical simulated
Giordano Beretta (HP Labs) Color Imaging XVII EI 2012 paper 8292-32 12 / 12