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Features
EIKONA FOR ARTS supports numerous color
transformations (namely RGB, XYZ, xyY,
UVW,uvY, U*V*W*,SthetaW, L*a*b*, L*u*v*,
YIQ, CMY, CMYK, HSI, HSV, HLS) that
can be used for colorimetry studies
of paintings. It contains tools for analyzing color
information (e.g.histograms, statistics).
EIKONA for Arts supports the registration
of different modalities of the same painting
(e.g. infrared/visible/X ray/ultraviolet)
images based on a set of user-defined feature
points that are given by mouse clicks.
Image superposition can be performed
by registering and superimposing two different
images (e.g. a visible and an infrared
image) of the same painting. Registration is
performed on two source images having
equal size, with the first image considered as
the reference image.Registration
produces an output image which is a scaled,
translated and rotated version of
the second source image, based on certain feature
points specified by the user. The
result of superimposing the registered version of the
latter image with the former exhibits
much better alignment characteristics.
The following images correspond to
the same painting, which is acquired in the visible
and x-ray regions of the spectrum
(from left to right, respectively):
(click for larger image)
Since acquisition systems are not perfect,
position misalignment may occur during the
acquisition of the x-ray image. Thus,
a point in the visible image may not correspond to
the same point in the x-ray image.
Detection of misalignment can be easily performed
by superposition of both images in
one color image. Hue shifts in the resulting color
image indicate regions of strong misalignment.
As an example, the color image that is
formed by the visible and x-ray images
is displayed below:
(click for larger image)
EIKONA FOR ARTS can perform mosaicing
of a set of digital images that have been
produced by using a camera positioning
system (e.g. EIKONA
for Arts/Capture). This
procedure can be applied to infrared
images (digital reflectography) or to color images
in the visible range in order to produce
high resolution images of a painting. EIKONA
FOR ARTS supports both options. Certain
image capture distortions can be tolerated.
The images to be mosaiced should contain
overlapping border regions. When
"automatic mosaic" option is chosen,
the software creates the mosaic automatically.
When "manual mosaic" is chosen, the
user defines feature pixels on mouse click that
are subsequently used for refining
the mosaic. Mixed manual/automatic mode is also
possible. The final result of mosaicing
is excellent.
Usually, high resolution acquisition
of a large painting is performed indirectly through
the acquisition of smaller, overlapping
regions (tiles) of the painting. For this purpose,
a camera is mounted on a positioning
unit which is controllable by a computer system.
The following figure represents an
example of this acquisition process, where four tiles
were generated.
Image processing methods can be utilized
to combine these tiles ("mosaicing") and
produce a high resolution digital
representation of the painting. The following figure
displays the result of the mosaicing
operation, when applied to the example of the
previous paragraph.
The images images captured by the infrared
camera system suffer from considerable
luminance and geometry deteriorations,
introduced by the camera lens and furthermore
by the construction of the camera
tube. Therefore, before the image mosaic an
intermediate stage is required, in
which the captured images are corrected, on the
basis of some other data collected
during the image capture stage.
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The luminance problems of the captured images may
be
significantly corrected, with the aid of two reference
images,
a black image and a white image, both captured immediately
after capturing the image frames. These two images
indicate
the problem areas, where the luminance of the captured
images
is distorted. |
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So, using these images further
corrections may be achieved,
providing improved results
for the final mosaiced image, with
minimal luminance transitions
from one image frame to the
adjacent ones.
The results of
this method are shown in the following images: |
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Apart from the luminance distortion introduced in
the captured
images, these images suffer also from various geometrical
distortions, which however can be corrected by using
a calibration
grid. This grid serves as a pattern in order to
recognize the
geometrical distortions and correct them afterwards.
So, before
the image mosaic this corrective step is neccesary,
in order to
achieve the best possible results.
Experimental results of this method
is shown below: |
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| Platform Availability |
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Microsoft Windows 95/98/Me/NT 4.0/2000/XP |
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Overview