Using 25 Megapixel CMOS Cameras for Metrology and Inspection Applications with Active Sensor Control

Posted by Gretchen Alper on Fri, Jul 12, 2013

An increase in resolution to a 25 Megapixel CMOS camera, can allow for a wider field of view (FOV), and better optical and/or measurement resolution. These cameras are a cost-effective way to make a performance leap in inspection and metrology systems. 

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Topics: Image Quality Improvements

Bayer Area Scan Color Cameras compared to 3-CCD Color Cameras, part 2

Posted by Gretchen Alper on Thu, May 16, 2013

With advances in filters, color processing, and overall sensor control by experienced camera designers, the shortcomings for single chip (Bayer filter mosaic) color cameras compared to 3-chip prism-based color cameras have nearly been eliminated.  We have compared the different technologies with regards to image quality and color fidelity.  Here we will compare with regards to costs and design.  For most outdoor applications, such as global security systems and intelligent traffic systems, the color accuracy achieved from Bayer area scan cameras is more than sufficient and the simplified camera design offers overall system advantages. 

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Topics: Image Quality Improvements

Adimec’s Industrial Imaging and Machine Vision Blog: Best of 2012

Posted by Gretchen Alper on Sun, Dec 30, 2012

It is that time of year again when we reflect on the past year, and plan for the next.  2012 was a big year for Adimec as we celebrated our 20 year anniversary.  Hopefully our blog has been a source of helpful information over the last year. 

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Topics: Interface Technology, CCD vs. CMOS, Image Quality Improvements

In-Field Calibrations for Optimal Machine Vision Image Accuracy

Posted by Gretchen Alper on Fri, Oct 12, 2012

Flat Field Correction (FFC) processing can be used to minimize or even remove artifacts to improve the image uniformity.  The purpose of flat field correction is to ensure image uniformity regardless of exposure.

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Topics: New Adimec Products, Image Quality Improvements

Color Images in Machine Vision: Advantages of In-Camera Processing

Posted by Gretchen Alper on Wed, Oct 3, 2012

When a full color image from the machine vision system is required for accuracy, there are several advantages for having color processing right in the camera.  But, creating color images you can rely on is not as easy as it seems, especially when the image must represent the actual color of the scene.

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Topics: Image Quality Improvements

How to Select the Best Industrial Camera: Are You Shot Noise Limited?

Posted by Gretchen Alper on Thu, Jun 21, 2012

When determining the best industrial camera, one of the first considerations is to determine if your application is shot noise limited.  This can help you prioritize the most important camera parameters, such as dynamic range or sensitivity. 

In this blog we explain how to determine if your imaging system is light limited or shot noise limited.

Shot noise originates from the discrete nature of electrons.

Consider the following example: imagine standing at an overpass above a highway and counting the amount cars passing by in one minute. The next minute, and the next, and the amount counted is probably not the same. The resulting measurement varies from minute to minute, following a Poisson distribution.

In the electron domain this is similar: the standard deviation of the amount of captured electrons in a pixel is the square root of the mean signal level.

The amount of electrons (signal level) depends on the QE and the amount of light (photons) that hit the sensor.

Where QE is Quantum Efficiency:  The probability that a photon that reaches the pixel will be converted into an electron.  The QE is the only camera parameter that shot noise SNR depends on.

Say that N is the amount of electrons in the pixel, then sqrt(N) is the shot noise that is on top. For an increasing amount of electrons, the shot noise increases as well.

Noise however should not be considered on its own. In applications, the noise has to be seen relative to the signal. In practice, the Signal to Noise Ratio (SNR) is used. In general the ‘noise’ is referred to as its RMS value.

Neglecting other sources but shot noise, the SNR is than N/sqrt(N) = sqrt(N).

The SNR increases for a larger signal! 

SNR-wise it is desired to accumulate as many electrons in the pixel as possible, which requires a large Full Well. However this is not always possible due to the limited amount of light.

The system is said to be light limited when, while not yet reaching saturation, the exposure of the sensor cannot be increased.

Large full well is not of the essence here where Full well is the maximal number of electrons that can be contained in the pixelOther performance parameters such as read noise and fixed pattern noise behavior are more important.

If more light can be captured (for example by increasing the integration time), the better the SNR becomes according to the equation. It does pay off here to use a sensor with a larger full well.

The system is said to be shot noise limited when there is an abundance of light and a large full well is desired to optimize it.

Free ePaper on How to Select the Best Industrial Camera - Click Below:

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Topics: Image Quality Improvements

See more details with HD cameras regardless of fog or hazy conditions

Posted by Gretchen Alper on Thu, May 3, 2012

At the SPIE Defense, Security, and Sensing 2012, Adimec demonstrated two technologies that are part of our rugged camera platform.

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Topics: Applications, Image Quality Improvements

Advantages of in-camera image processing: How camera technology makes a better picture part 2

Posted by Gretchen Alper on Thu, Oct 27, 2011

To continue our discussion on the ways camera technology can make a better picture, we offer a recent story from a customer regarding the advantages of in-camera image processing.  This particular example relates to Flat Field Correction (FFC) functionality.

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Topics: Image Quality Improvements

Image Sensors vs. Cameras, how does camera technology make a better picture?

Posted by Gretchen Alper on Thu, Oct 20, 2011

OEM system developers typically consider industrial video cameras that contain a particular image sensor, and then base their final decision on baseline needs such as camera outline and unit price.  While the image sensor selection is important, the fact that several cameras use the same image sensor does not mean the cameras from different vendors will produce the same image, or even meet the requirements of specific vision applications.  But what parameters are determined by the camera and how can you determine the right fit for your system?  

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Topics: Sensor Technology, Image Quality Improvements

Minimized Channel Matching Error on Cameras with Kodak Sensors

Posted by Gretchen Alper on Wed, Jul 6, 2011

Channel matching error or channel mismatch is defined as the difference between the CCD sensor outputs at a certain video level.  We work to ensure our channel matching error is as small as possible and that the channel matching is automatically maintained despite changes in temperature. 

A dual tap CCD sensor allows for the image to be split in half (or in 4s for a quad tap sensor) so that the charge transfer can be completed much more quickly (Figure 1).  One of the side effects of using a dual tap camera is a channel mismatch.  Channel mismatch is visible as a difference in offset, linearity, or sensitivity of the two image haves (Figure 2).

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Topics: Image Quality Improvements