Looking for information on the ColorChecker?
Here you will find:
April 2012: Complete Web page update and new content. Average data (Excel file) from 30 charts and updated images. eciRGB_v2 data is now computed instead of eciRGB Version-1 data. We have added descriptions and images of the various ColorChecker charts formats (Classic, Proof, Passport, Mini).
April 2009: Added a file in CxF2 (CxF Version-2) format which contains both the averaged data and the X-Rite reference.
March 2007: Added visual comparisons between measured data and the average chart.
June 2006: Average data from 20 charts and updated images (now also in 16-bit format).
coordinates of the ColorChecker" PDF was updated
and augmented; it now presents a detailed comparative analysis
of the latest (2005) reference data, provided by GretagMacbeth, against the
results derived from our spectral average.
Click on any line of the following list to go directly to the section of interest:
Attention ! Warning ! Important ! Read-me !
This page is not really related to BabelColor. Well, it is in the sense that BabelColor software is well adapted to view, measure (on display or prints), extract from images, and compare ColorChecker targets. It is not related in the sense that the ColorChecker is the main subject of the page, that many products from other companies are mentioned, and because of the less informal tone used in the presentation.
In fact, this page, on-line since 2004, simply exists because of my longtime interest in the ColorChecker.
But before we continue, just a small formality: ColorChecker is a Registered Trademark of X-Rite, and X-Rite is a Trademark. OK, back to the ColorChecker!
The ColorChecker Color Rendition Chart, this very well known chart with an array of 4 x 6 color patches, is an icon of the imaging industry. It was presented in a 1976 article (this is more than 35 years ago!) by C. S. McCamy and his colleagues from the Macbeth Company, a Division of Kollmorgen Corporation at the time:
Below, on the left, is a photograph of Mr. McCamy
with the ColorChecker during a visit at the Munsell Color Science Laboratory, in
2002. In previous versions of this Web page, I challenged readers to try to improve it. This is a tricky image to
correct; it is a JPEG made under fluorescent lights which was somewhat
auto-corrected in the camera. Three reader submissions are shown, below on the
right, in a composite image.
The ColorChecker is now sold by the Munsell division of X-Rite. Here is a timeline of how Macbeth, Munsell and X-Rite are related (principal info source: Macbeth Lighting History):
The ColorChecker consists of a series of six gray patches, plus typical additive (Red-Green-Blue) and subtractive (Cyan-Magenta-Yellow) primaries, plus other "natural" colors such as light and dark skin, sky-blue, foliage, etc. The color pigments were selected for optimum color constancy when comparing pictures of the chart with pictures of the natural colors... as reproduced on color film! Optimizing the human visual match was thus not the first priority; still, it was shown, by the chart designers, that the degree of metamerism was also very small when directly comparing the chart to the natural colors. Expressed otherwise, the perceived colors of the ColorChecker vary in the same way as the natural colors they represent when the light source changes*, either when imaged on film or compared directly.
Traditionally seen in photography magazines, in articles dealing with color film rendition, the chart has found a renewed interest with the advent of digital cameras. In view of what was mentioned above relative to the ColorChecker being optimized for film based reproduction, it could be argued that this optimization would not be ideal for the sensors of these new cameras. However, because the imaging sub-systems of all digital cameras are specifically designed to mimic the response of the human visual system, there is no major reason why the ColorChecker's natural color patches should not be trusted as valid substitutes for their natural counterparts in various lighting conditions**. And what about the other non-natural colors, the additive and subtractive primaries, and the gray scale patches, which are not designed to be equivalent to a particular real-life color? They were valid then, and they still are. In reality, the patches of a color chart do not need to be surrogates of natural objects to make them useful, but the fact that some of the ColorCheker patches can be used in such a way is a definite plus.
As many of us know, the various brands of digital cameras are like film; each has its own color rendering characteristics, which is constantly modified by automatic white balance software within the camera. Basically, the accuracy of the colors at the output is a moving target. The problem is such that many high end cameras provide a way to get the "raw" measurements extracted from the camera sensor, without any processing; the file format is not surprisingly called "RAW" (RAW as in non-gamma-corrected, non-color-corrected, high resolution - much more than 3 x 8-bit RGB - data from the camera sensor). The user can then manipulate the data and try to extract accurate color information over a wide dynamic range. Where we just had to take the picture and let the photo finisher color balance our print, we now have to process the colors ourselves; such is progress....
One way of helping the process of obtaining color fidelity is to
use the ColorChecker as a target within the scene. Other charts with more
patches have been devised, the ColorChecker Digital SG first comes to mind, but this simple chart satisfies the needs of many
since you can make a rapid judgment by just looking at it. To illustrate how
much we "know" this chart, here are four targets with the first three
being only different layouts of the original ColorChecker, and the fourth
one, a representation of... the Datacolor
SpyderCheckr, a direct competitor of the ColorChecker Passport, also
with dedicated software, but manufactured in a larger format.
The first target shows patches sorted in a* (the a* of L*a*b*, from green to red, and from top to bottom, then left to right); the second one is the usual ColorChecker layout, and the third one shows patches sorted in hue (the h* of L*C*h*). The first and third layouts do not look as familiar, but you may hesitate a moment when looking at the last target on the right which has very similar colors and slight layout changes in the first and third rows (Note: The third patch of the first row looks brownish in some Datacolor images, and greenish in others; the colors used for this image are the reference sRGB colors from Datacolor).
For many years, the ColorChecker was available only in two formats: a "standard" chart approximately "letter size" (the standard North-American writing paper size), and a smaller format about the size of a business card, called "Mini". These two formats are now called "Classic". In addition we can now find the ColorChecker in other sizes or with additional patches for specialized applications. Here is a short description of the formats which is followed by images of the charts.
Before the Internet, it was quite difficult to find where to buy the chart. With the wide spread of the Web plus the renewed interest due to digital cameras, it can be found at many places. We used to provide a list of a few dealers but it is now easier to locate a supplier with the following options:
It is important to mention that we see no significant statistical differences in the colors of the patches measured on two ColorChecker Passport and two ColorChecker Proof relative to the average previously measured with a mix of 20 ColorChecker and Mini ColorChecker. This is why the data from ColorChecker Passport and ColorChecker Proof targets was incorporated in the average of 30 charts.
However, the data presented here is still not valid for the ColorChecker Digital SG.
Measurement geometry: 45 deg./0 deg. for all data sets. The illumination is an inverted light cone hitting the color patch at 45 degrees and the measurement is taken perpendicularly to the patch, at zero degree. This configuration is such that the specular (i.e. mirror-like) reflection from the light on the patch surface is not directed back on the sensor, and is thus less sensitive to gloss; this is the preferred geometry for printing applications. Please note that this geometry is considered the same as when the Illumination hits the target perpendicularly and the measurement is taken at 45 degrees (i.e. 0 deg./45 deg.).
Measuring instruments: 24 of the 30 data sets were measured with Eye-One Pro spectrocolorimeters from X-Rite/GretagMacbeth, three with the X-Rite DTP20 (Pulse), two with the GretagMacbeth Spectrolino/Spectroscan, and one with the X-Rite DTP22 (Digital Swatchbook). The DTP20, DTP22, and Spectrolino/Spectroscan are now discontinued. The 24 Eye-One Pro used in this compilation were a mix of Rev-A to Rev-D instruments, manufactured between 2003 and 2011, with most of them non-UV cut (although this has no effect on the measurements since the ColorChecker pigments are not fluorescent). None of the measurements were derived with the X-Rite XRGA protocol, a protocol designed to improve inter-instrument agreement between many legacy and current X-Rite and GretagMacbeth instruments; announced in 2010, XRGA is progressively being integrated in X-Rite products. As per X-Rite XRGA Web page, the changes induced by the XRGA protocol should be minimal. In April 2012, X-Rite has announced the availability of the Eye-Pro 2 (i1Pro 2), which replaces the original Eye-One. Based on the same measurement geometry and as the model it replaces, the i1Pro 2 has new and improved features, one of them being the capability to support the M0/M1/M2 Measurement Conditions as defined in ISO 13655. When making measurements of the ColorChecker with the i1Pro 2, the M0 condition should be selected as it is equivalent to what we obtained with the older Eye-One, and is still perfectly adequate for non-fluorescent substrate measurements.
The first document is a tutorial-type article which presents the RGB coordinates of the ColorChecker patches in 4 common RGB spaces: Apple, Adobe (1998), ProPhoto and sRGB (Note: Additional data for these and 15 other RGB spaces can be found in the spreadsheet below). The coordinates were derived from the GretagMacbeth (2005) L*a*b* D50 reference data and from the averaged spectral measurements (of 20 charts); the two data sets are compared against one another and against other references, such as the 1976 McCamy article. For those who want to dig deeper, this document also describes the data conversion procedures and presents all the required equations.
The second document contains numerical data and graphs. The average data derived from measurements is now from 30 charts. For those who have downloaded the previous spreadsheet (issued in 2006) which contained average data from 20 charts, you will notice that the average data from 30 charts shows minor changes and no surprises; the changes affect about half of the patches, with one or two RGB component changed by 1 unit (in 8 bit). However, even if these changes are minor, we have updated the images from the averaged data to match the newly computed values.
The two following documents contain ColorChecker data in industry standard file formats that can be opened by software.
Most ColorChecker owners will have a need for the actual RGB values of the patches at one time or another. This used to be hard to find information since, until late 2005, the RGB values provided with the chart corresponded to no known RGB space. The only reliable reference data was xyY coordinates determined with Illuminant-C, as they appeared in the 1976 McCamy article.
It was, and still is, possible to find, on the public Web and in scientific sources, published data obtained by people who measured their chart. While OK in principle, this is not enough (for me at least). How old was the chart? Is the chart representative of the production average? How precise was the measuring instrument? Was the instrument calibrated? How was the data processed afterwards? Should I say more? These and other factors make the results of a single measurement unreliable.
This was the justification to write the first version of the "RGB coordinates of the Macbeth ColorChecker" pdf. This was also the reason behind the project to average spectral data provided by chart owners.
Why is spectral data important? Because spectral information gives you the capability to determine the color coordinates as seen under any illuminant, and thus any RGB space, with more precision.
Analysis of the spectral data also gives some hints that various pigments are/were/could-have-been used to manufacture the charts. This figure shows two types of spectrums seen for the light-skin patch; these two types are seen with both the Standard and Mini charts, with either new or somewhat older (3 years +) charts. Other patches show a similar behavior. It is important to note that these different spectrums do not necessarily result in distinctly different colors (or color coordinates) and other factors contribute to make the spectral data more fuzzy, such as storage effects, frequency of use/light exposure, and chart edition (manufacturing variability). One of the nice surprises in this analysis is that the charts seem to age very slowly when kept in dark storage and used on an occasional basis, which is the case for most serious amateurs and pros. A 12 years old chart (well kept, I insist) has 23 patches out of 24 within the standard deviation!
One of the patches that varies the most is the White one, as can be seen in the Standard deviation table of the spreadsheet. I have recently seen a white patch, from a never-used ColorChecker Proof (i1Publish), which is quite yellow (L*a*b* D50, average of 3 measurements: 96,48/-0,53/5,84) even if it was always kept in its black paper sleeve; however, it is impossible to say if this yellowing is due to the sleeve or if this is a statistical outlier, since other ColorChecker Proof were close to the computed average. In any case, the white patch is not the most neutral of the gray ColorChecker patches and the third neutral patch from the left is often recommended to perform gray balance.
When this project began, we could compare only the data derived from the 1976 McCamy article to a handful of average measurements. Because experimental measurements with a few samples cannot be considered reliable, I placed, at the time, more importance on the data derived from the article than on the measured data. As the number of charts measured grew, it became obvious that the measured data was getting stable but still different from the original reference values. While the accumulating evidence was that user measurements were a more accurate assessment of the "average" chart than the data in the 1976 article, RGB coordinates and images (synthetic charts) determined using both approaches were made available on this site, at the time, so that users could select the ones they preferred.
Around October 2005, GretagMacbeth updated its reference data on the ColorChecker and made it publicly available (ColorChecker reference pdf from the ColorChecker Classic page on the X-Rite Web site). This data includes L*a*b* D50 and sRGB values. However, they did not include RGB values for Adobe(1998), ProPhoto or any other RGB space.
This "new" GretagMacbeth L*a*b* D50 data matches the average measurements very well. On the other hand, both the average measurements and the new GretagMacbeth data do not match that well what was derived from the xyY coordinates of the 1976 article. These comparisons are discussed further in the "RGB coordinates of the Macbeth ColorChecker" pdf. As a result, I now consider the 1976 data as obsolete; nonetheless, for completeness, the coordinates derived from the 1976 data can still be found in the Excel spreadsheet presented above.
In the "RGB coordinates of the Macbeth ColorChecker" article, the GretagMacbeth L*a*b* D50 data is used to derive the RGB coordinates for Adobe(1998), Apple, ProPhoto, and sRGB (even if coordinates for this last space are proposed by GretagMacbeth). Of course, the RGB coordinates obtained from the averaged measurements are also provided for comparison purposes. In addition, the RGB data is presented in both 8-bit and 16-bit format, the later in full precision, not just a multiple of the 8-bit format, i.e. not just 8-bit values x 256.
Finally, while the match between the RGB coordinates derived from the GretagMacbeth L*a*b* D50 data and the RGB coordinates determined from the average spectral measurements is quite good, the match between the sRGB values given by GretagMacbeth and the sRGB coordinates determined from average measurements is not as good. The results show it is likely that the GretagMacbeth sRGB data was derived from another data set than their L*a*b* data; much more details on this analysis are given in the pdf. I thus recommend the sRGB coordinates derived from GretagMacbeth L*a*b* D50 to the sRGB coordinates given by GretagMacbeth.
As for which data I think is better, the data from the average measurements or the new GretagMacbeth values, here are suggestions:
PatchTool screenshots above are examples of
individual charts compared to the average of 20 charts. The first
example is from the chart whose average error is the smallest relative to the
average chart, i.e. the "best". The second screenshot compares a typical "middle
of the pack" chart to the average, i.e. the "median". The third one compares the
chart which is the most different from the average, i.e. the "worst". In these
screenshots, each square is made of two triangles such as this one:
For many patches, especially the ones of the "best" and the "median" charts, the triangles cannot be distinguished since the difference is very small; enlarging the chart so that it fills the screen will help, as well as taking the time to look for differences (5 to 10 seconds for each patch). To help classifying the patches, colored borders are added when color difference thresholds are exceeded. These borders are yellow and red in the above examples, with the yellow border applied to all patches whose difference is larger than the value assigned to the lower threshold but smaller or equal to the higher threshold, and the red border applied when the color difference exceeds the higher threshold. In practice, 50% of the charts should be similar to, or better than, the median chart, with essentially one or two color differences which are more easily noticeable.
The next three screenshots respectively show the standard deviation in Lightness (L*), Chroma (C*), and hue (h*) computed from the 20 charts. The top triangle shows the average value minus the standard deviation, and the bottom triangle shows the average value plus the standard deviation. For a given screenshot, only one parameter is different, either L*, C*, or h*, and the other two are the same. Expressed in terms of statistics, there is 68% probability that your chart patch is between the top and bottom triangle for this parameter.
As we see in the screenshots, the Lightness variation is the most important factor, followed by Chroma, then hue. The Chroma and hue differences are particularly small and difficult to notice. In the third screenshot, all neutral patches are assigned a red border, corresponding to an apparently large standard deviation in hue higher than 20, even though the difference is not visually noticeable; this is expected for very neutral tones, near the illuminant, for which the Chroma (saturation) is very low.
Finally, to get an idea of the maximum color difference that you could encounter between your ColorChecker and the average values, we used the CIEDE2000 color difference formula and, for each patch, compared the average value (click here for the average file) to the individual data of the 20 charts. We then selected the "worst case" for each patch, and built a composite color list (click here for the "worst case" file); this list is made of patches from 12 of the 20 charts (i.e. all the patches of the other 8 charts are better than these worst cases). The top triangle is the "BabelColor Average" patch, and the bottom one is the "worst case" patch. Please note that the "worst case" patches are NOT representative of the statistical "standard deviation", which is much less, as can be seen in the three screenshots just above.
You will (hopefully!) never obtain a comparison as in this worst case screenshot when comparing your chart to the average, since a typical chart may contain between zero and four similar patches, and finding between 0 and 2 is more likely. Also, you will note that six patches have a CIEDE2000 color difference of less than one, which is excellent, especially considering these are the "worst cases"!
Click on one of the following ColorChecker icons to see the image, or right-click (control + click on a one-button Mac mouse) to download the linked file or the target. The QuickTime plug-in may be required to view TIF images in a browser, which will not show the colors correctly anyway since these images have NO embedded profiles. In addition, 16-bit TIF files are not well supported in Web browsers. It is thus strongly recommended to first download these images and open them in a graphics editing program afterwards:
The "Derived from GretagMacbeth L*a*b* D50 data" images were obtained by starting with the data published by GretagMacbeth in 2005, i.e. L*a*b* D50, which was converted to D65 with the Bradford Chromatic adaptation matrix when required, and finally converted to RGB. Because, as we mentioned, these images have NO embedded profiles, each of them should be assigned its respective RGB space profile (the Adobe RGB profile to the Adobe file, etc.) using Photoshop or any other program which can assign a color profile to an image. RGB coordinates tables for these and fifteen other spaces are also available in an Excel spreadsheet.
The "Derived from the spectral average of 30 charts" images were obtained by averaging the data sent to me by YOU! This data was extracted from the spectrums of all the ColorChecker charts formats presented above except the ColorChecker Digital SG. RGB tables for these four spaces and fifteen other spaces are also contained in the Excel spreadsheet.
Note for 16 bit images: The 16 bit RGB and L*a*b* images were obtained programmatically from the spreadsheet data values since it is not possible to assign 16 bit colors in most image processing software. While these are full 16 bit images, the colors in these images will only be quantified in 15 bit+ by Photoshop; please consult the PatchTool Help manual for more information on the 15 bit+ vs 16 bit formats. A 16 bit image can easily be generated by PatchTool; you first need to import a 16 bit RGB color list, a L*a*b* color list, or a file with spectral data such as the "CC_Avg30_spectrum_CGATS.txt" file available above, then export as an image in 16 bit TIF format.
Note for L*a*b* images: The L*a*b* images may show color values slightly different from those in the spreadsheet; these differences are usually not perceptible except perhaps for 8 bit images. For instance, it is not possible to assign a L*a*b* D50 value of (81, -1, 0) in 8 bit L*a*b* (you can try this in Photoshop!); this is due to how L*a*b* values are encoded in TIF files (in particular, the increments are not integers).
Not decided on which image is better? Read this.
These images and spreadsheet could be updated as I get more data. Thanks in advance!
If you are not satisfied by the looks of the chart image on your display, you are not the only one! This is not a new problem, as you can read in this 2004 article, Colour & Computers, by Charles Maurer, in Tidbits, an online publication for the Macintosh internet community which is in its 22nd year! His article has a few paragraphs on his experience of the various renderings of the ColorChecker chart obtained with different flavors of the sRGB profile and different applications. Monitor technology and software have changed, but not our requirements. Nowadays, we can work with wide-gamut displays with built-in Look-Up-Tables bundled with colorimeters and custom calibration software, from NEC and Eizo for instance, which are close to perfect. Even an entry-level display calibrated (i.e. profiled) with an entry-level colorimeter will provide a tremendous improvement in color accuracy and image editing efficiency.
You can contribute to this study if you have a ColorChecker chart, and if you can generate a spectral data file from a spectrophotometer. I will compile the results and make them available on this page. If you have a colorimeter with which you can measure only the color coordinates, without spectral data, well, send your data also!
Suggested file formats: CGATS (ASCII text
file format, often with a *.txt extension, used by Measure Tool,
and PatchTool), *.cxf
(Version-1 or 2, but not 3; CxF is an XML format used by Eye-One Share and other GretagMacbeth
software), *.xls (standard Microsoft Excel format that can be exported by
Eye-One Share), and any other standard
text based file format (*.txt or other) from any other software/spectrophotometer.
Please send the file at the following address (click the button to send an e-mail): .In your e-mail, include any pertinent information such as the chart format, its age (edition date written on the reverse or on the product package, or purchase date, even approximate), the chart condition, and some measuring instrument info (model, illuminant, software with version number, etc.).
Using the chart to auto-correct images or make ICC or DNG profiles
Because the ColorChecker patches cover a relatively large color gamut, not with a lot of samples mind you, one could think of using it to generate a correction profile, and the chart can effectively be used to generate an ICC profile or a DNG camera profile. It could be argued that making an ICC profile with a ColorChecker is foolish, but it is certainly better than no calibration at all. For many years it was possible to make scanner, monitor, printer and camera profiles using the ColorChecker with ProfileMaker Pro and MonacoPROFILER; unfortunately, it is only possible to make such profiles for printers in i1Profiler, the software that has replaced both ProfileMaker and MonacoPROFILER. Nowadays, the ColorChecker is more targeted ;-) for the creation of DNG profiles. DNG profiles can be used in Adobe® Imaging solutions including Lightroom®, Photoshop®, Photoshop® Elements, and Camera Raw (ACR). As well, its gray patches can be used for gray/white balance, to correct color casts or bad lighting. Here is a list of software that perform such tasks:
DNG Camera profiles:
White/Gray Balance (using a single neutral patch):
With all the above software, you generate your color correction transform or profile by incorporating the ColorChecker card in your photographed scene, and by analyzing the chart patches in the resulting image (this also works for calibrating a scanner). They are best used when you can manually adjust and freeze your digital camera white balance. If your digital camera does not enable you to control white balance, then you may still obtain good results if the lighting AND the color content of your scenes do not vary too much. These tools can also be used with traditional film if the lighting conditions do not change during the photo session (the white balance does not change in a traditional film, it is just not balanced!). Of course, you need a new profile each time you change the lighting conditions, and some may feel that generating and managing many ICC profiles--lighting does vary a lot--could become cumbersome. Having a set of transforms, as with Picture Window Pro. or an automated script, such as ACR Calibrator, are two alternatives to eliminate that burden.
Of course you do not absolutely need a ColorChecker to calibrate RAW files, as you can manually tweak the RAW import parameters. This method, however, can be more demanding than the ones presented above, and it is important to note that RAW files are NOT standardized, with each digital camera company proposing its own variant, some of them proprietary (see the OpenRAW web site for more info on this potential problem). Adobe has proposed the "public" Digital Negative (DNG) archive format to address the issue. In any case, using the ColorChecker within your images, as part of the RAW file manipulation process, or with any other file format, will definitely provide helpful visual feedback.
Even with all these tools, there are pictures which remain difficult to correct. Cal McCamy's picture shown above is one such case. Taken under fluorescent lighting and saved under a JPG format, it cannot be corrected with a simple click. The old adage which says that it is preferable to place a filter on the lens than to correct the picture afterwards applies here; however, such filters are not universal to all types of fluorescent lamps (and there are many) and are simply not part of most photographers' accessory bag.
Using the chart to analyze your camera's performance
If you want to check the accuracy of a ColorChecker image, and thus the accuracy of a camera profile or of the correction procedure applied to an image, you can use PatchTool's Extract Target from Image tool, designed specifically to extract the average of target patches in full size photographic images. This tool can accommodate targets of any size in almost any position, and can easily be configured to extract a ColorChecker. The supported image formats are TIFF RGB (8 bit and 16 bit), and JPG. Embedded profiles are recognized and automatically extracted.
To measure your camera's color quality, noise, and tonal response, you can use the Colorcheck module of the Imatest program offered by Norman Koren. The Colorcheck program uses images of the ColorChecker chart to perform its analysis. Use this program to check how the automatic white balance feature of your camera is working.
The other Imatest modules are dedicated to measuring the sharpness and gray response using other types of targets (you can print some of the targets). This program is becoming a reference for digital camera analysis, as can be seen on the imaging-resource.com site.
Note: If you are interested in photography in general, and in its technical aspects in particular, you have to go on Norman's namesake site, www.normankoren.com, where you will find some of his images, which can be purchased, and a tremendous amount of free technical info on digital photography.
The problem with the ColorChecker Digital SG
The ColorChecker SG is a chart dedicated to digital photography. It has a Semi-Gloss finish with highly saturated colors. On the chart Web page we read that its features include "24 patches from original ColorChecker," and the corresponding patches are laid out on the SG chart in the same configuration as in the standard ColorChecker. Many would assume, by the layout and these words, that they are the same, but this is not the case since the semi-gloss finish introduces measurable differences.
Here is a file with spectral data of the ColorChecker Digital SG, in CGATS format (a human readable text file); the origin is unknown but is likely from GretagMacbeth: Digital ColorChecker SG.txt
Except for the bluish-green, white and four gray patches, all the other patches are relatively far from the original chart colors (with an average DeltaE*ab difference of about 7 with the standard ColorChecker). This has been confirmed from measurements on two charts (the measured values of these two charts are very close to one another however, which is good since it shows manufacturing consistency). Because of this, it is not recommended to use the spectrums or the RGB and L*a*b* values given in this page for comparison with the "equivalent" patches of the ColorChecker Digital SG chart. Note: these comments have nothing to do with the quality or utility of the card per se.