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I-Cube
Intro Brochure
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I-CUBE offers turnkey systems
custom designed to be
"out of the box" solutions for specific customer applications,
priced no higher than the cost of individual components.
- Imaging products are chosen to both meet specific customer
application requirements AND to work seamlessly together
- Computer system components are selected to optimize compatibility and performance
- All software, hardware, and drivers are installed and the system
tested to ensure optimal performance
- Systems are tested and shipped complete, enabling the customer to simply set it up upon
receipt and begin productive work almost immediately - we even
include cabling diagrams and custom setup instructions when
applicable
Customers make only one call for technical support, eliminating integration headaches
and finger pointing among component vendors.
Measuring
of fibre orientation in nonwovens using image processing |
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By : S.
Hariharan, S. A. Sathyakumar, P. Ganesan |
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The
standardized index of dispersion was tested on real as
well as simulated patterns by dividing the patterns
into quadrats of different areas ranging from 2 mm2 to
100 mm2. For a given quadrat size and number, the same
image was sampled multiple times by shifting the
position of horizontal grid lines by a known amount
(10% of height) in the downward direction (CD) while
keeping the column positions constant. This was done
to minimize the dependence of dispersion index on
quadrat positioning, which could potentially render
the same pattern clumped or uniform. The variance and
mean of all samplings were pooled to evaluate the
standardized dispersion index and dispersion
anisotropy. Statistical stationarity of images was
assumed during multiple samplings of the same image.
The dispersion evaluation algorithm was implemented
using FORTRAN 90, and critical values of χ2
distribution were evaluated using IMSL routines.
Images of webs were taken using digital cameras with
field of view at least 5 cm x 5 cm. Nonwoven webs were
imaged under reflected white light with a resolution
of 84 pixels/cm. Colored images were converted to
gray-scale using digital color separation that kept
the channels having maximum amount of intensity
information (evaluated using information
entropy).Histogram equalization (flattening) was done
to remove any illumination intensity variation within
and between images. Removal of illumination variation
(lighting instability) via histogram flattening
improves the repeatability of data. In all images,
lighter regions represented denser regions of webs.
Dispersion evaluation was then performed on the
preprocessed images.
Uniformity evaluation was performed on four simulated
patterns and four nonwoven webs. Figure 5 shows a
simulated 30 gsm, 4.1 denier, continuous fiber web,
while Figure 6 shows a simulated 20 gsm, 10.5 denier,
staple fiber web. Both simulated images had a
resolution of 500 pixels/cm. Of the four nonwoven webs
tested, there were two spunbond (15 gsm and 60 gsm),
one carded-thermobond (31 gsm), and one spunlace (58
gsm) nonwoven.

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Our
Web site is packed with information on our product lines. We invite
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License Plate Recognition
License Plate Recognition for a wide
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vehicles & alarm when Wanted Vehicles detected.     
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IMAGE ANALYSIS Solutions
How we test:
Camcorders
Digital camcorders have brought high-quality video capture to the masses,
but not all models are equal. If you're looking to buy a video camera, you
know there are a lot of specs listed on the box. Unfortunately, they won't
tell you what you really need to know, which is how good the footage of
your daughter's birthday party, your brother's wedding, or your first
independent short is going to look. There's only one way to find out, and
that's to shoot a lot of footage under a variety of conditions and take a
careful look at the results. We test camcorders in our camera lab under
controlled lighting conditions so that we have a solid basis for comparing
different models. Under indoor-color-balanced tungsten lighting, we shoot
sample footage of our carefully created scene, which contains a diversity
of colors, contrast, textures, and patterns. Under daylight-color-balanced
HMI lighting, we shoot a series of test targets to determine how well a
camcorder deals with important image-quality challenges such as noise,
accurate color reproduction, and sharpness. Then we take the camcorders
out in the field to see how they'll perform in typical shooting
conditions.
Image-quality tests
Noise test
The laws of physics dictate that it is impossible to digitally capture an
image that is completely free of noise.
Although, the larger the physical size of a sensor is (not the
number of pixels), the less susceptible a sensor usually is to noise.
Numerous other variables impact how noisy digitally captured footage can
be, including a camcorder's optics and integrated post-processing
capabilities.
To evaluate the amount of noise generated by a camcorder, we start by
capturing footage of an X-Rite
Munsell ColorChecker Chart target (formally known as the GretagMacbeth
ColorChecker Chart) using daylight-balanced
HMI lighting. The camcorder's white-balance setting is set to either
daylight or automatic, depending on which one is more color-accurate. Then
we extract still frames, and analyze the images using Imatest
image-analysis software to measurably evaluate the generated quantity of color
and luminance noise.
The footage is captured at the lowest-available compression setting, and
at the camera's highest native
resolution.
Color reproduction ability test
While color can be corrected via software after video is captured by a
camcorder and copied over to a computer, it's usually best to start with
captured footage that is as color-accurate as possible--especially for
those instances when the footage will not be edited or might be burned
directly to disc.
To evaluate how well a camcorder can reproduce accurate colors, we capture
footage of the X-Rite Munsell ColorChecker Chart target using
daylight-balanced HMI lighting. Footage is captured at the camcorder's
daylight white-balance setting. We then extract still frames and analyze
the images using the Imatest image-analysis software in order to
measurably evaluate a camcorder's ability to reproduce colors correctly.
The footage is captured at the lowest-available compression setting and at
the camera's highest native resolution.
Sharpness test
The potential sharpness of an image is directly impacted by the resolution
of the sensor that captured the image. However, several other variables
impact the overall sharpness of a digitally captured image, especially the
quality of a camcorder's optics and its integrated postprocessing
capabilities.
To evaluate how well a camcorder can create sharp images, we capture
footage of an ISO
12233 test target using daylight-balanced HMI lighting, with the
camcorder set to automatic white balance. We then extract still frames and
analyze the images using the Imatest image-analysis software to measurably
evaluate a camera's capability when capturing sharp details. The footage
is captured at the lowest-available compression setting, and at the
camera's highest native resolution.
Tungsten lighting tests
In our camera lab, we shoot a fixed scene made up of objects with a wide
range of colors, textures, and reflective properties. The video is shot
under color-balanced (centered around 3,200K), tungsten studio lights. We
use the camcorder's automatic exposure and set the focal length of the
lens to a point in the middle of the zoom range for these tests. We set
the camcorder to its highest-available quality setting, and test with
three different white-balance settings:
- Automatic white balance
- Manual white balance
- White balance preset for tungsten or indoor lighting
We also test a camcorder's low-light capability by shooting the scene lit
by only a shaded lamp with a 150-watt incandescent bulb. We use the
automatic white-balance setting during this part of the test and cycle
through all special low-light modes available on the camera.
In addition to the video created in our camera lab, we shoot video in both
indoor and outdoor settings. We shoot various scenes in a variety of
lighting situations, capturing footage that contains a diversity of
colors, contrast, patterns, and light levels. We also shoot video that
includes people with a variety of skin tones in order to evaluate how well
a camcorder captures them.
We evaluate the quality of the video for sharpness, detail, proper
exposure, accurate color reproduction and saturation, white-balance
accuracy, dynamic range, and tonal separation. We also look for typical
problems that arise with camcorder footage, including image noise,
artifacts, and lens distortion. All of the footage is reviewed on a
professional video monitor.
If the camcorder offers still-image capture to a flash memory card, we
follow our standard procedures for testing digital
still cameras and capture photos for evaluation in addition to the
video.
Image-quality characteristics
Here are some examples of the image-quality characteristics we consider
when evaluating a camcorder.
White balance
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The sample at the top left has correct white
balance; the whites and grays look neutral, and there's no
discernible color cast. We consider the sample on the bottom left
acceptable. Even though the image appears a bit too cool (bluish)
and measurements indicate that the blue channel is a bit too
strong, it still lacks an obvious color cast. The incorrect sample
on the top right has an obvious, distracting color cast. |
Exposure
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The top left and right samples are overexposed
and underexposed, respectively. Using the correct exposure on the
bottom left as a reference, you can see that in the overexposed
sample, the sky looks blown out, and you can't tell that there's a
glass wall on the right side because it loses the reflection. The
underexposed version loses detail and definition in the white
pipes. |
Color saturation
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The sample to the immediate left most accurately represents our
test scene. The sample on the top left has undersaturated colors;
it looks as if there is a smoky filter in front of the scene. The
sample on the top right is oversaturated, with colors that look
too vivid to be real. |
Dynamic range
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We use various techniques to evaluate dynamic range,
but these are two quick indicators: to judge quality of shadows,
you should be able to clearly see the gorilla's face and the
various shades of brown that comprise it. For good highlights, you
should see well-defined reflections off the CD and the detail of
the hat's weave. |
Noise
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The top left and right examples respectively show low and high
noise, and the sample to the immediate left displays moderate
noise. The noise in these samples appears as white spots. We
consider the quality of the first sample to be good, the second
unusable, and the third acceptable. |
Testing equipment
CALL Barry
on +27 31 764 3077 or + 27 (0) 82-562-8225 or E-Mail NOW
(info at I-Cube dot co dot za) OR
Fax Number :
0866539659 OR Contact one of our DISTRIBUTORS
or an independent
security advisor!
I-CUBE and PlanetCCTV
announce a partnership whereby
the I-CUBE Facial and LPR products will now be shipped PRE-installed on
all PlanIT CCTV products Please download
(ZIP
/ Word)
the I-Cube
Company Profile and Products if you require more information
I-Cube. All rights reserved.
Revised: February 18, 2008
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