We have developed an algorithm for recording multiple gradated two-dimensional projection patterns in a single three-dimensional object. When a single pattern is observed, information from the other patterns can be treated as background noise. The proposed algorithm has two important features: the number of patterns that can be recorded is theoretically infinite and no meaningful information can be seen outside of the projection directions. We confirmed the effectiveness of the proposed algorithm by performing numerical simulations of two laser crystals: an octagonal prism that contained four patterns in four projection directions and a dodecahedron that contained six patterns in six directions. We also fabricated and demonstrated an actual prototype laser crystal from a glass cube engraved by a laser beam. This algorithm has applications in various fields, including media art, digital signage, and encryption technology.
We have developed an algorithm for recording multiple gradated two-dimensional projection patterns in a single three-dimensional object. When a single pattern is observed, information from the other patterns can be treated as background noise. The proposed algorithm has two important features: the number of patterns that can be recorded is theoretically infinite and no meaningful information can be seen outside of the projection directions. We confirmed the effectiveness of the proposed algorithm by performing numerical simulations of two laser crystals: an octagonal prism that contained four patterns in four projection directions and a dodecahedron that contained six patterns in six directions. We also fabricated and demonstrated an actual prototype laser crystal from a glass cube engraved by a laser beam. This algorithm has applications in various fields, including media art, digital signage, and encryption technology.
The image projected by a three-dimensional object varies depending on the projection method
and the angle of the projection axis. Figure 1 shows that a single
central object can project three distinct patterns, the characters “X”,
“Y”, and “Z”. In this example, parallel projection is used, and the
three projection axes are mutually orthogonal. A similar object that contains the projection
patterns of the characters “G”, “E”, and “B” is depicted
on the cover of the book, “Gödel, Escher, Bach: An Eternal Golden Braid”1. We see, therefore, that three two-dimensional information patterns can be
recorded in a single three-dimensional object. Multiple patterns can be thus recorded in a
three-dimensional object by solving the relevant eigenvalue problems. It is possible to
project different binarized images on three axes by this technique2. However,
the combination and the number of patterns that can be recorded are limited and each pattern
is a binarized image. For example, this method cannot record the combination of characters
“I”, “I”, and “I” in a single three-dimensional
object.
Figure 1
Three patterns (characters “X”, “Y”, and “Z”)
projected by a single central object.
The algorithm proposed in this paper allows any number of patterns and almost any pattern to
be recorded in a single three-dimensional object. The most significant characteristic of this
algorithm is that the projection patterns are not required to be binary, but are allowed to
have gradation. A projected pattern is recognizable because its signal is stronger than the
extraneous information, which is treated as background noise.
Results
Numerical simulation
We performed computer simulations for two laser crystals: an octagonal prism with four
patterns and four projection axes and a regular dodecahedron with six patterns and six
projection axes. Each pattern consisted of 64 × 64 pixels, and the voxel values were
given by the crack density at each point. In the prism, the volume included a total of
493,169 cracks and for the dodecahedron it was 494,464. In both cases, we determined that
no meaningful information could be seen outside of the projection directions, i.e., when
the object was viewed from an angle that was not in line with a projection axis. Also, in
both cases, although the projected patterns were a little noisy, nevertheless, they were
quite recognizable as the intended patterns.Figure 2 shows the results of a computer simulation for a laser
crystal made from an octagonal prism with four projection axes. Figure
2(a) shows the prism from an angle that is not in line with a projection axis,
and this illustrates that no meaningful information can be seen outside of the projection
directions. Figure 2(b) shows the four patterns that were used.
Figure 2(c)) shows the patterns that were reconstructed by
projections from the volume. Figure 2(d) shows the results of a
computer simulation for a laser crystal made from a regular dodecahedron with six
projection axes. Figure 2(e) shows the dodecahedron from an angle
that is not in line with a projection axis. Figure 2(f) shows the
six patterns that were used. Figure 2(g) shows the patterns that
were reconstructed by projections from the volume.
Figure 2
Computer simulations for two laser crystals (three-dimensional glasslike volumes): an
octagonal prism with four patterns and four projection axes and a regular dodecahedron
with six patterns and six projection axes.
(a) View of the octagonal prism from an angle that is not in line with a projection
axis. (b) Four original patterns, each consisting of 64 × 64 pixels. (c) Four
images reconstructed by the octagonal prism and obtained from views normal to the
direction of the surface. (d) View of the regular dodecahedron from an angle that is not
in line with a projection axis. (e) Six original patterns, each consisting of 64 ×
64 pixels. (f) Six images reconstructed by the regular dodecahedron and obtained from
views normal to the direction to the surface.
The images used in the simulations were original and the pictures which were from a
standard test image database.
Prototype of a three-dimensional laser crystal
Figure 3 shows the actual prototype of cubic three-dimensional
laser crystal with three projection axes. Figure 3(a) is the view
from an angle not in line with a projection axis. We can observe no meaningful information
outside the appropriate axis direction. Figure 3(b) presents the
three original patterns, each of which consists of 64 × 64 pixels. Figure 3(c) shows the photographs obtained from views normal to the surface. The
cubic laser crystal has side of 6 cm and contains 492,719 cracks. The patterns are
recognizable as the original pattern. Note that this is an example of a volumetric
display34.
Figure 3
Cubic three-dimensional prototype laser crystal with three projection axes, sides of
6 cm.
(a) View of the three-dimensional laser crystal from a direction not in line with a
projection axis. (b) Original patterns, each consisting of 64 × 64 pixels. (c)
Photographs of images reconstructed by the laser crystal and obtained from directions
normal to the surface. (This is linked to the accompanying animation.)
Discussion
We developed an algorithm for recording multiple two-dimensional projection patterns in a
single three-dimensional object, although work still needs to be done to improve the quality
of the resulting images. We have already begun this work. Specifically, we have added steps
to the proposed algorithm for both preprocessing and postprocessing the images. The most
important information is usually in the centre of the screen. Although it is desirable that
the background noise be uniformly random, irregularities will occur in practice. In the
preprocessing step, we make the noise distribution uniform in the centre of the image by
sacrificing the quality at the edges. First, we calculate the volume containing multiple
two-dimensional patterns. Secondly, we rearrange the pixel values in each reconstructed
pattern so that each pattern becomes clearer in the centre at the expense of clarity at the
edges. Then, we calculate the volume again. In the postprocessing step, the noise signals
are overlapped in the direction of the axes. Each voxel value is obtained from the density
of points in the laser crystal. In the original algorithm, the points are placed at random
in each voxel. In the postprocessing step, we rearranged the points within the voxel so that
the noise points are lined up with the projected pattern. By applying these steps, the peak
signal-to-noise ratio (PSNR) improved from 10 dB to 30 dB.We think that this technology is applicable to digital signage5. Since
computerization is important if this is to be used as a display system, we have also
developed some electronic systems that make use of the proposed algorithm. One is a cubic
display consisting of full-colour light-emitting diodes (LEDs) in an 8 × 8 × 8
array. Figure 4(a) shows the system from a view that is not in line
with an axis, and thus there is no recognizable pattern information. However, from the front
view of the system shown in Fig. 4(b), we observe “20”,
and “13” (this year is 2013) can be seen in the side view shown in Fig. 4(c). We made another volumetric display system, this one based on a
7 × 7 array of threads6, in which a laser illuminates each thread.
Figure 4(d) shows the system from a view that is not in line with an
axis. Figure 4(e) shows the front view, and Fig.
4(f) shows the side view.
Figure 4
Two types of electronic volumetric display systems.
(a) A system made of full-colour LEDs seen from a view not in line with an axis. (b)
Front view of (a). (c) Side view of (a). (d) A system made of threads seen from a view
not in line with an axis. (e) Front view of (d). (f) Side view of (d). (These are linked
to the accompanying animations.)
An electronic display system such as this can project an image in any direction, and the
proposed algorithm limits the range in which the image is seen. In other words, it can
determine the direction in which the image is projected. Using this property, it is possible
to send visual information to only one specific person. As shown in Fig.
5, the system can track a specific person and project information that will be
visible only in that direction. The proposed algorithm allows this to be done for multiple
people and multiple images. In practice, this may work in situations where movement is
controlled, e.g., airplanes, escalators, moving sidewalks, or trains.
Figure 5
Projection system sending picture information to a specific person.
Our method can also be used for encryption. Here, the most important feature of the
proposed algorithm is that we cannot recognize meaningful images when we observe the volume
from other than the image-projection axes. To take advantage of this feature, we have
applied the proposed algorithm to double-random-phase optical encryption7.
Figure 6 shows the proposed encryption system that includes our
algorithm. In the typical double-random-phase approach, the input image is two dimensional.
However, we can regard the laser crystal as a point cloud, and instead of a two-dimensional
image, we use the proposed algorithm to record images at random positions and at a random
angle on the laser crystal. We treat as keys the position and angle of the image on the
laser crystal/point cloud. In this way, we have a system that is more secure than the
typical double-random-phase approach.
Figure 6
Double-random-phase optical encryption using the proposed algorithm.
This proposed algorithm can expect to find applications in many fields, including media
art, digital signage, and encryption technology. In the near future, we hope to report
further developments in the applications mentioned above.
Methods
One volume containing three patterns
We begin by describing the method for recording three projection patterns, as shown in
Fig. 7. In Fig. 7(a), we see that three
original patterns, A, B, and C, are located on different axes and are incorporated in a
single three-dimensional object. The patterns can be obtained as images in, for example, a
bitmap image file (BMP format). The parameters a,
b, and c are the pixel values of the respective
patterns. The recording space consists of P × Q × R voxels. The blue lines in
Fig. 7(b) represent lines from the voxel centre perpendicular to
the original patterns. Each voxel value V is defined by where λ is a constant used to adjust the total
intensity. Three original patterns are recorded by calculating all the voxel values in the
volume. The densities of the projected patterns from the volume constructed by equation (1) can be represented by
The values in parentheses are changed by varying
the indices i, j, and k in the above equations. When the changes of
the values in parentheses are relatively uniform, they can be treated as constants on the
level of perception. Thus, the projected patterns are recognizable as the original
patterns due to visual processing in the brain that compresses the image by removing
high-frequency components8.
Figure 7
Schematic diagram depicting the recording method for three dimensions.
(a) The sizes of three original patterns. (b) Three original patterns are combined in a
central rectangular solid that consists of P × Q × R voxels. (c) Example of
calculating λ.
A concrete way of calculating of λ is explained with the aid of Fig. 7(c). Suppose there are three pictures, A, B, and C, each of which consist
of four pixels. The numbers in the figure show the pixel value of each picture. The values
of A, B, and C are then
calculated as follows from equations (2) toWhen , the image of a is in
agreement with the original picture. However, it is difficult to obtain a value of
λ for which for all i and
j. Thus, instead, λ is set to the reciprocal of the average of all the
pixel values. Consequently, the variation in the pixel values is decreased, and the
high-frequencies can be deleted. The value of λ in this example is as follows:
One volume containing N patternsThe above algorithm can be easily extended to N dimensions . The green lines in Fig. 8 represent
projection axes. If the projection axes are not parallel, the original patterns are recorded in the central volume consisting of
voxels. As there are an infinite number of nonparallel axes, in principle, it is possible
to record an infinite number of original patterns.
Figure 8
Extension to N dimensions (N = 1, 2, 3, 4...).
Any number of original patterns can be
recorded if the projection axes are not parallel.
As in the general case, the value of each voxel V is defined by where
represent the pixel values of the points at which lines from the voxel centre
perpendicularly intersect the original patterns. As above, λ is a constant used
to adjust the total intensity. The N original patterns are recorded by calculating
all the voxel values in the volume.As an example, we will consider pattern P(1) (see Fig. 8). The
projected pattern density is the summation of the voxel values in the normal direction:
When the values in parentheses in equation (6) are relatively uniform, they can be treated as constants on
the level of perception. Thus, the projected patterns are recognizable as the original
patterns, just as in the three-dimensional (N = 3) case.
Author Contributions
H.N. and T.I. suggested this technique. A.S. and N.M. wrote the main manuscript text. R.H.
and T.S. prepared Figs. 4,5,6. All authors reviewed the manuscript.