Convert an 8 or 16 bit per component TIFF image of a test chart
into .ti3 device values
using automatic pattern recognition, or manual chart alignment.
Performs other tasks associated with turning a TIFF raster of test
patches into numeric values.
usage: scanin [options] input.tif
recogin.cht valin.cie [diag.tif]
'input.tif', and outputs scanner 'input.ti3', or
usage: scanin -g [options] input.tif
:- outputs file
usage: scanin -o [options] input.tif
:- outputs file
usage: scanin -c [options] input.tif
recogin.cht scanprofile.[icm|mpp] pbase [diag.tif]
pbase.ti2 and outputs printer pbase.ti3, or
usage: scanin -r [options] input.tif
recogin.cht pbase [diag.tif]
pbase.ti2+.ti3 and outputs pbase.ti3
a chart reference (.cht) file
patch values in .val file
image to measure color to convert printer pbase .ti2 to .ti3
as -c, but accumulates more values to pbase .ti3
device values in pbase .ti3
is to create a scanner .ti3 file
auto recognize, locate using four fiducual marks
for perspective distortion
chart in normal orientation only
is to recognize all possible chart angles
true mean (default is robust mean)
Approximate gamma encoding of image
generate diagnostic output (try -dipn)
- B&W of input image
- Horizontal edge detection
- Vertical edge detection
- Groups detected
- Lines detected
- All lines detected
- lines used to improve fit
- lines perspective corrected
- lines rotated
- sample boxes rotated
- sample box outlines
- sample box names
- sample box areas
- pixel areas sampled
outputfile Override the
default output filename & extension.
Usage Details and Discussion
scanin is setup to deal with
a raster file that has been roughly cropped to a size that contains
the test chart. It's exact orientation is not important [ie. there
is usually no need to rotate or crop the image any more finely.] The
reference files are normally set up with the assumption that the
edges of the chart are visible within the image, and if the image is
cropped to exclude the chart edges, it may well not recognize the
chart properly. It is often better to crop out anything outside the
chart itself (i.e. labeling text, logo's below the chart etc.) It is
designed to cope with a variety of resolutions, and will cope with
some degree of noise in the scan (due to screening artefacts on the
original, or film grain), but it isn't really designed to accept
very high resolution input. For anything over 1200 pixels on a side,
you should consider down sampling the scan using a filtering
down-sample, before submitting the file to scanin. Similarly, any
file with a large level of noise (due to screening or scanner
artefacts, or a noisy surrounding texture) should consider cropping
out the noisy surrounding, or down sampling the image or filtering
it with some average preserving filter before submitting it to
scanin. Examining the diagnostic output (ie. -dig and -dil) may help
in determining whether noise is an issue. To check that the chart
has been correctly recognized, use -dipn and examine the diag image.
There are 5 basic modes that scanin operates in.
A number of flags and options are available, that are independent of
the mode that scanin is in.
- When no special argument is given scanin is
assumed to be parsing an input device characterization chart
(ie. an IT8.7/2 chart), for the purpose of creating a .ti3 data file containing
the CIE test values and the corresponding RGB scanner values.
The .ti3 file can then be
used for creating an input profile using colprof.
The file arguments are: The TIFF file that is
to be processed, the image recognition
template file, the CIE reference value
definitions for the test chart (sometimes labeled a ".q60"
file), and an optional name for the image
recognition diagnostic output. The resulting .ti3 file will have
the same base name as the input TIFF file.
- If the -g flag is specified, then
scanin is operating in a mode designed to create the necessary
image recognition template file (.cht) boilerplate
information. Patch location and labeling information would need
to be added manually to such a generated file, to make a
complete and useable recognition template file. CHT file format. The input TIFF
file in this situation, should be a good quality image, perhaps
synthetically generated (rather than being scanned), and
perfectly oriented, to make specification of the patch locations
easier. The file arguments are: The TIFF file
that is to be processed, the image
recognition template file to be created, and
an optional name for the image recognition diagnostic output.
- If the -o flag is used, then scanin
will process the input TIFF file and produce a generic CGATS style file
containing just the patch values (a .val file). The file arguments are: The TIFF file that is to be processed, the image recognition template file to be
created, and an optional name for the image
recognition diagnostic output.
- If the -c flag is used, then an input
image of a print test chart can be used in combination with a
device profile, to estimate the CIE tristimulus values of the
patches. This allows RGB input devices to be used as a crude
replacement for a color measuring instrument. The icc or mpp
profile has (presumably) been created by scanning an IT8.7/2
chart (or similar) through the RGB input device, and then using
scanin to create the .ti3 file needed to feed to colprof to
create the input device profile. The file arguments in -c mode
are: The TIFF file that is to be processed
containing the image of a print test chart, the
image recognition template file for the test chart generated by
the printtarg tool, the input device ICC or MPP profile, the base name for the .ti2 file containing the
test chart printer device values and their patch identifiers and
the base name for the resulting .ti3 file, and
finally an optional name for the image recognition diagnostic
output. The resulting .ti3 file will have the same base name as
the input TIFF file. If there is more than one page in the test
chart, then scanin will need to be run multiple times, once for
each scan file made from each test chart. The
-ca flag combination should be used for all pages after
the first, as this then adds that pages test values to the .ti3
file, rather than creating a .ti3 file that contains only that
pages test values. If the incoming .ti2 file contains
per-channel calibration curves, these will be passed through to
the .ti3 so that accurate ink limits can be computed during
- If the -r
flag is used, then the input TIFF value is used as a source of
device values to replace any existing device values in the given
.ti3 file. This is intended for use in the situation in which
the device values being fed into an output device are altered in
some way that is difficult to predict (ie. such as being
screened and then de-screened), and this alteration to the
device values needs to be taken into account in creating a
profile for such a device. The file arguments in -r mode are: The TIFF file that is to be processed
containing a rasterized image of an output test chart, the image recognition template file for the
test chart generated by the printtarg
tool, the base name for the .ti2 file
containing the output test chart device values and their patch
identifiers and the base name for the .ti3 file that is to have
its device values replaced, and finally an
optional name for the image recognition diagnostic output.
Normally scanin will try and recognize a chart, irrespective of its
orientation. For charts that have some asymmetric patch size or
arrangement (such as an IT8.7/2, or a chart generated by printtarg with the -s option),
this is both flexible and reliable. Other charts may be symmetrical,
and therefore having scanin figure out the orientation automatically
is a problem if the recognition template does not contain expected
patch values, since it will have an equal chance of orienting it
incorrectly as correctly. To solve this, the -a
flag can be used, and care taken to provide a raster file that is
within 45 degrees of "no rotation".
Normally scanin will use automatic chart recognition
to identify the location of the test patches and extract their
values. If the chart CHT file
has four fiducial marks defined, then the chart can be manually
aligned by specifying the pixel location of the four marks as
arguments to the -F flag. The top left,
top right, bottom right and bottom left fiducial marks X and Y
co-ordinates should be specified as a single concatenated argument,
separated by comma's, e.g: -F 10,20,435,22,432,239,10,239 The
coodinates may be fractional using a decimal point. Four fiducial
marks allows for compensation for perspective distortion.
By default the automatic chart recognition copes
with rotation, scale and stretch in the chart image, making it
suitable for charts that have been scanned, or shot squarely with a
camera. If a chart has been shot not exactly facing the camera
(perhaps to avoid reflection, or to get more even lighting), then it
will suffer from perspective distortion as well. The -p
flag enables automatic compensation for perspective distortion.
Normally scanin computes an average of the pixel
values within a sample square, using a "robust" mean, that discards
pixel values that are too far from the average ("outlier" pixel
values). This is done in an attempt to discard value that are due to
scanning artefacts such as dust, scratches etc. You can force scanin
to return the true mean values for the sample squares that includes
all the pixel values, by using the -m
Normally scanin has reasonably robust feature
recognition, but the default assumption is that the input chart has
an approximately even visual distribution of patch values, and has
been scanned and converted to a typical gamma 2.2 corrected image,
meaning that the average patch pixel value is expected to be about
50%. If this is not the case (for instance if the input chart has
been scanned with linear light or "raw" encoding), then it may
enhance the image recognition to provide the approximate gamma
encoding of the image. For instance, if linear light encoding
("Raw") is used, a -G value
of 1.0 would be appropriate. Values less than 2.2 should be tried if
the chart is particularly dark, or greater than 2.2 if the chart is
particularly light. Generally it is only necessary to provide this
is there are problems in recognizing the chart.
The -v flag enables extra verbosity in
processing. This can aid debugging, if a chart fails to be
The -d flag enables the generation of an
image recognition diagnostic raster. The name of diagnostic raster
can be specified as the last in the command line, or if not, will
default to diag.tif.
Various flags control what is written to the diagnostic raster. Note
that at least one flag must be specified for a diagnostic raster to
i creates a black and
white version of the input raster in the diagnostic output, to be
able to compare with the feature extraction.
h will show pixels in the
input image classified as being on horizontal edges, in red.
v will show pixels in the
input image classified as being vertical edges, in green.
g will show groups of
pixels that will be used to estimate edge lines, each group in a
l will show valid lines
estimated from the vertical and horizontal pixel groups, in white.
L will show all lines
(valid and invalid) estimated from the vertical and horizontal pixel
groups, in white.
I will show valid lines lines
used to improve the final fit, in blue.
c will show the lines with
perspective correction applied in cyan.
r will show the lines
rotated to the reference chart orientation, in yellow.
s will show the diagnostic
sampling box edge outlines, rotated to the reference chart
orientation, in orange.
o will show all the
sampling box edge outlines, in orange.
n will show the ID names
of the sampling boxes, plus the diagnostic sample boxes, using a
simple stroke font, in orange.
a will show the sampling
areas as crossed boxes, plus the diagnostic sample boxes, in orange.
p will show the sampling
areas as colored pixels.
The combination of -dipn is usually a good place to start.
The TIFF file can be either 8
or 16 bits per color component, with 16 bit files being slower to
process, but yielding more precise results.
If at all in doubt that the file has been recognized correctly, use
the -dipn diagnostic flag
combination, and check the resulting diagnostic raster file.
[ A badly recognised image will typically result in high self fit
delta E's when used with colprof. ]
parameter allows the output file name & extension to be
specified independently of the last tiff filename. This works for
the default, -g and -o modes. It is ignored for the -r, -c and -ca
modes that use a basename for .ti2 in and .ti3 output. Note that the
full filename must be specified, including the extension.