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With PrimoPIX Primo is setting new standards in the
field of video camera technology for security applications.
The innovative sensor concept of PrimoPix technology is based
on the most up-to-date »Digital Pixel System® (DPS)« platform.
With this technology, the picture information of each individual
pixel is converted digitally at the point of capture and
processed in the most optimal way. Therefore, even situations
with a great range in contrast can be recorded and documented
in picture qualities previously unseen.
With this UWDR technology (Ultra Wide Dynamic Range), the
Primo cameras have the advantage over all previously known
processes in that they can display considerably more details
in shaded and very bright sections of a picture. The latest
generation of high-resolution sensor technology also provides
clear, high-contrast and color-true pictures without any blooming
or smearing even in the most difficult lighting conditions,
e.g. against strong backlighting, in conjunction with the software
developed especially for the security field.
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NO SMEARING |
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High contrast
& color accuracy |
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Discover the powerful technology of PrimoPix and its unique
picture quality. We’ve compared high-quality CCD
cameras with our PrimoPix in various surveillance scenarios.
The test shows our camera’s conclusive superiority
in coping with even the most extreme lighting conditions
and constant changing environment.
Judge for yourself!
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ATM MACHINE |
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Convenience
Store |
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Ocena Port |
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Facial
Recognition |
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Casino |
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Train Station |
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Parking
Garage |
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The core invention in DPS (Digital Pixel System) is
the inclusion of an analog-to-digital converter (ADC) within
each pixel of the image sensor. The ADC translated the light
signal into a digital value at the immediate point of capture,
thus minimizing signal degradation and cross-talk in the
array and allowing for greater noise reduction methods. Once
the data is captured in a digital format, a variety of digital
signal processing techniques are used for optimal image reproduction.
PrimoPix DPS technology uses a technique known as “multi-sampling” to
gather the information to achieve unmatched image quality and
high dynamic range. Each pixel is independently sampled non-destructive
multiple times in a single capture frame (which in video is
typically 50 or 60 times per second). The imaging system determines
the optimal time to sample and store the pixel information
before the pixel is saturated and can no longer hold additional
charge. In the graphic on the bottom, the light pixel is saved
at time T3, the latest sample time before it saturates at 100
percent. The dark pixel builds up charge more slowly and uses
additional time until it is sampled and stored at T5. The stored
values of information (intensity, time, noise offset) captured
at each pixel are then processed in parallel and converted
into high-quality images. In contrast, other technologies typically
set one exposure time for the frame and sample each pixel at
that time-resulting in images with some pixels that are underexposed
(too dark) and some that are overexposed (too bright).
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Because each pixel has its own analog-to-digital converter
and the information generated is captured and processed independently,
each pixel in effect acts as its own camera. The exposure
time for each pixel is adjusted to handle the unique lighting
conditions at that pixel location in the image sensor array.
A product built with the Digital Pixel System platform essentially
has hundreds of thousands of individual cameras, each of
which produces the best image possible. These images are
then combined to create a high quality video frame or picture.
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The digital image sensor and digital image processor function
much like the eyes and brain in humans, with two-way real-time
interactivity to capture the highest quality image possible.
Just as the brain of a person walking into a dark room instructs
the eyes to open the pupil to allow in more light, the digital
image processor loads new code into the sensor to alter not
only exposure times but the actual image capture algorithms.
The result: the best possible picture given the specific
image characteristics and lighting conditions.
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