Sample Measurement Technique in Digital Color Communication

Before any permanent samples are measured and stored into the computer database or communicated digitally, a repeatable measurement technique must be established and observed.  Samples should always be measured multiple times with the largest area view available on the spectrophotometer being used as long as the samples are large enough to completely cover the viewing area.  Spectrophotometers typically come equipped with a range of aperture sizes to allow measurement of both small and large samples, though it is always preferable to use the largest aperture size possible to minimize the influence of unlevel dyeings.  Smaller ports may be used as necessary for measuring even the smallest of samples.  Physical standards should be prepared with the intention of using the largest area view available on the spectrophotometer in order to improve upon the repeatability of the digital color data.  Samples measured with small apertures will require additional reads to insure minimal measurement error.  After establishing an appropriate measurement technique, the details must be communicated clearly to everyone involved in color measurement, not only internally but throughout the supply chain.



Sample Thickness


Two to four layers will be sufficient for most knitted and woven materials to achieve an opaque sample for presentation to the instrument.  If the material is not opaque, light will pass through the sample and reflect off the backing material or sample holder and produce misleading reflectance data.  Of forty cotton-poplin test samples measured with four layers and then remeasured with two layers to determine opacity effects, Table 1 lists the eleven samples that show a color difference of greater than DE CMC (2:1) 0.15.  These samples should therefore be measured using four layers, as their digital data will be influenced by the color of the sample holder or backing material.  As a precaution and to eliminate the time and effort to perform opacity tests, the majority of samples should be folded to four layers even though they may be opaque at two layers.



DE CMC (2:1) D65/10
10 Red 0.18
12 Orange 0.18
13 Light Orange 0.31
15 Light Brown 0.19
16 Beige 0.31
17 Medium Yellow 0.56
18 Dark Yellow 0.25
20 Mint 0.21
24 Light Green 0.26
37 Medium Grey 0.17
40 Cream 1.07


Table 1. Color Difference for Non-opaque Samples


Lightweight and translucent materials will often require so many layers to become opaque that the material is forced into the interior of the instrument when measuring, producing an inaccurate reflectance measurement.  For these types of materials, repeatable results can be obtained by measuring only a few layers of material backed with a white ceramic tile similar to the instrument’s calibration tile.  The portion of the reflectance due to the color of the backing will be factored out when comparing two samples if the backing is the same for both.



Sample Positioning


Sample rotation and repositioning will reduce measurement variability due to fabric construction, directionality of yarns, and unlevel dyeings.  A common practice in sample measurement is to place the sample at the instrument port and simply rotate the sample for four or more measurements.  This technique allows for fast measurement, but it will not account for variations due to unlevel dyeing and should be avoided.  A better technique is to remove the sample from the instrument and refold or reposition it before additional readings.  Care should always be taken to avoid any areas of the sample that are contaminated by dirt, fingerprints, creases, dye blotches, or other substances.



Developing a Repeatable Technique


An optimum measurement technique has been established when a sample can be measured, removed from the instrument, and then remeasured with a variation of less than 0.15 DE CMC (2:1).  Higher variation will decrease the confidence level in the quality of the stored data and lead to less accurate match predictions.


A simple technique for determining the correct number of measurements to make is to first produce an average reading for a sample by measuring it eight times – being sure to rotate and reposition the sample after each read – and saving the average.  This should produce the most repeatable read even though it is not practical for day-to-day operations.  Remove the sample and then measure it again using the same technique – eight reads with rotation and repositioning.  The color difference between these two averages should be very low.  Remove the sample and then measure it again, but this time use only seven reads with rotation and repositioning.  Repeat the process using six reads, five reads, four reads, three reads, and finally two reads.  After obtaining color difference data between each test and the original sample measured eight times, identify the point at which the DE CMC (2:1) exceeds the desired limit of 0.15.  As an example, if the DE CMC (2:1) of the four read sample is 0.08 and the DE CMC (2:1) of the three read sample is 0.21, samples should be read four times to ensure a variation of less than 0.15 DE CMC (2:1).  When the correct number of reads has been determined, measure the sample at least four more times using the required number of reads to confirm that all reads are less than 0.15 DE CMC (2:1).  If any of the measurements are greater than 0.15, the technique must be altered either by modifying sample placement or by taking additional reads.



Measurement Repeatability Evaluation


Measuring a sample three or more times may seem too time consuming, but the time taken in the beginning to ensure accurate measurements will translate into reliable color differences when comparing standards and batches and when communicating digital color data.  The measurement speed of modern spectrophotometers will reduce the time required to make additional reads to only a few seconds.  The following tables have been prepared to provide information regarding typical measurement variability that may be expected when taking multiple readings of various fabric types.



Four-Read Variability Two-Read Variability
1 Light Red 0.08 0.12
2 Pink 0.03 0.02
3 Light Red 0.03 0.10
4 Burgundy 0.07 0.05
5 Bright Red 0.02 0.19
6 Cherry Red 0.03 0.31
7 Melon 0.05 0.21
8 Lt Rose 0.03 0.13
9 Peach 0.03 0.05
10 Red 0.04 0.42
11 Dark Orange 0.04 0.09
12 Orange 0.02 0.09
13 Light Orange 0.02 0.16
14 Dark Brown 0.03 0.09
15 Light Brown 0.04 0.11
16 Beige 0.02 0.06
17 Medium Yellow 0.05 0.05
18 Dark Yellow 0.01 0.09
19 Lime 0.02 0.14
20 Mint 0.01 0.12
21 Dark Green 0.03 0.14
22 Medium Green 0.01 0.09
23 Medium Grey 0.07 0.11
24 Light Green 0.01 0.37
25 Jade 0.01 0.38
26 Medium Blue 0.01 0.05
27 Medium Blue 0.05 0.36
28 Bright Blue 0.01 0.10
29 Dark Navy 0.05 0.17
30 Navy 0.01 0.44
31 Dark Blue 0.01 0.03
32 Maroon 0.02 0.81
33 Purple 0.01 0.11
34 Light Violet 0.02 0.18
35 Pink 0.03 0.04
36 Fuchsia 0.05 0.02
37 Medium Grey 0.03 0.24
38 Black 0.01 0.16
39 Tan 0.01 0.04
40 Cream 0.02 0.04
Average 0.03 0.16
Max 0.08 0.81
> 0.15 0 13


Table 2.  Measurement Variability for Four-Read and Two-Read Techniques


Table 2 lists the DE CMC (2:1) color differences in D65/10 obtained when performing repeat measurements using both a four-measurement technique and a two-measurement technique with a 30mm large area view aperture.  Samples were folded to four layers to ensure opacity and were repositioned and rotated 90° between measurements.  Thirteen of the forty test samples showed variability greater than 0.15 DE CMC (2:1) when using the two-measurement technique.  The average repeatability for the four-measurement technique was 0.03 with a maximum of 0.08, while for the two-measurement technique the average was 0.16 with a maximum of 0.81.  It can be concluded from these results that digital color data produced using a two-measurement technique – even when using a large aperture – is not reliable.


In Table 3, standards of various fabric types were measured using a 20mm aperture designated MAV for medium area view and a 9mm aperture designated SAV for small area view.  The same sample was then remeasured using four, three, and two readings and compared to the standard to produce the DE CMC (2:1) values listed.  All samples except corduroy were measured using two layers with repositioning and 90° rotation between measurements.  The DE CMC (2:1) values represent the maximum observed color difference for several repeat measurements of the various materials, though lower values were also observed.  Columns displaying a dash (-) indicate that no tests were performed, as results for the higher number of measurements were already unacceptable.  For each of the materials tested, the appropriate number of measurements to use must consistently produce measurement variation of less than 0.15 DE CMC (2:1).


MAV:  20mm                            SAV:  9mm

Fabric Type 4 3 2   4 3 2
Woven Twill, Canvas, Crepe, Poplin 0.03 0.10 0.10 0.05 0.12 0.11
Satin, Taffeta 0.07 0.07 0.09 0.11 0.12 0.20
Seersucker, Wafflecloth, Ribstop 0.09 0.10 0.13 0.07 0.10 0.18
Brushed Terry, Napped (non-fleece) 0.04 0.07 0.07 0.14 0.17 0.23
Corduroy 0.13 0.31 0.64 0.55
Knit Interlock, Pique, Jersey 0.12 0.11 0.16 0.14 0.13 0.20
Thermal, Narrow Rib 0.05 0.12 0.13 0.07 0.18 0.24
Pointelle 0.17 0.20 0.23 0.60
Popcorn Knit, Pleated 0.03 0.07 0.07 0.04 0.27 0.20
Fleece (brushed/napped side) 0.11 0.12 0.19 0.15 0.40 0.46
Chenille, Panne 0.08 0.11 0.12 0.56
Mesh 0.03 0.07 0.12 0.14 0.21 0.35
Wide/Variegated Rib 0.20 0.30 0.51 0.30 0.68


Table 3.  Measurement Variability for Various Fabric Types


Use of a larger aperture such as the 30mm large area view will produce lower DE CMC (2:1) values as the area of measurement is significantly increased.  Large aperture sizes may only be used however when measuring large samples that completely cover the aperture opening when using two or more layers, though one layer may provide acceptable results for opaque materials.


Failure to establish a repeatable measurement technique will introduce a significant potential for error into all aspects of color development and communication.  A repeatable measurement technique includes specification of the number of layers of material to use, the positioning of samples, the number of measurements to make, instrument settings, and clear communication with the system operators.  Failure to fully test and confirm the quality of a measurement technique will be a source of error for the life of the program.  While the tables above may be used as a guide for the number of measurements required on most materials to obtain repeatable results, it is recommended that system users evaluate their own specific materials to confirm the final established measurement method.

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Ken Butts