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Sensor Cover Glass Removal: Machine vision camera customization for enhanced accuracy

Posted by Gretchen Alper on Tue, Nov 1, 2011

Standard image sensors found in industrial cameras come ‘of the shelf’ and can have limitations that can stand in the way of optimal performance, accuracy, and application-usefulness. As a result, it is often necessary to customize the sensors to meet specific system requirements.  Addressing certain aspects of sensors is a way how experienced camera manufacturers can customize cameras to meet the different needs of measurement methods.  In a previous blog we talked about our willingness to modify the anti-reflection coatings on sensors to improve performance at a desired wavelength.  Today we announce our full support of another modification option (cover glass removal) to eliminate limitations of the sensor design.

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Topics: Image Quality Improvements, Optical Enhancements

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

How to Measure the Fixed-Pattern Noise in Dark or DSNU: Repost from Harvest Imaging

Posted by Gretchen Alper on Tue, Oct 25, 2011

Last week, we wrote about the differences between the camera and the image sensor and what camera manufacturers can do to improve image quality.  We have also talked about compensating for artifacts in the sensorFixed-pattern noise is one such sensor imperfection which refers to the non-uniformity between pixels.  It can be described by two parameters DSNU (dark signal non-uniformity) and PRNU (photo response non-uniformity).

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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

Why the Modulation Transfer Function – MTF - also matters with camera selection, especially in NIR

Posted by Gretchen Alper on Mon, Sep 12, 2011

The Optical Transfer Function (OTF) is an important specification of lens performance. The OTF describes both the amplitude and the phase of a signal. In most cases the former, most times indicated as is Modulation Transfer Function (MTF), suffices. Modulation, as it is a measure of the modulation depth (contrast) of an optical signal. The MTF is for that reason sometimes also called Contrast Transfer Function (CTF).

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Topics: Vision System Optimization, 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

In-camera Color Processing from a Mosaic Color Filter Array (e.g. Bayer)

Posted by Gretchen Alper on Thu, Jun 9, 2011

For certain imaging applications, a full color image is required for accuracy, particularly with outdoor applications, such as traffic systems (license plate recognition), surveillance, and situational awareness.  Adimec’s color cameras can include in-camera color processing which we developed ourselves to be optimized for automated adjustment to ever-changing outdoor conditions. 

Color processing is optimized to bring human color perception from a screen-image as close as possible to color perception when looking at the actual scene.  Adimec’s color cameras utilize single chip digital image sensors with a Bayer CFA for cost and response reasons. The filter pattern is 50% green, 25% red and 25% blue.  (This is also discussed in our previous blog post).  With Mosaic Color Filter Array, color processing involves 2 steps:  demosaicing and then color recalculation.

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Topics: Image Quality Improvements

The Pros and Cons of Color Processing with Machine Vision Cameras

Posted by Gretchen Alper on Wed, Jun 8, 2011

Often color processing is desirable when a user is viewing the images rather than a machine, such as with the outdoor applications of traffic monitoring or surveillance.  Color processing can be done via the frame grabber or right in the camera.  This recent blog post on chipsight.com, which we have reposted below, provides some examples and the pros and cons of raw images versus color processed images.  Adimec color cameras have Bayer color filter arrays and can provide raw or RGB data to meet the needs of the specific application.

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Topics: Image Quality Improvements

Looking through the fog in HD resolution with cost effective visible camera solution

Posted by Gretchen Alper on Wed, May 4, 2011

See Through the Fog with Cost Effective Solutions for Defense and Security Applications from Adimec:  HD Doesn’t have to be High Cost

SWIR and infrared cameras enable "sight" in difficult situations for the human eye.  But these solutions offer low resolutions and a SWIR camera can cost 4 to 5 times more than a "normal" visible camera.  During last week's SPIE Defense, Security and Sensing event in Orlando, FL, Adimec showed our VEM technology and our new rugged camera platform.  This technololgy enables contrast enhancement using visible cameras with high resolution (e.g HDTV) to obtain clear images despite environmental issues such as fog, mist, or low light.  The combination of high resolution and the ability to see clearly in difficult circumstances significantly improves the possibilities for detection, recognition, and identification in situational awareness and HD designator systems.

That’s why Adimec’s  “See Through the Fog” demo really struck a chord:

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Topics: Image Quality Improvements

In-camera Video Contrast Enhancement To See Through the Fog

Posted by Gretchen Alper on Wed, Apr 27, 2011

Adimec’s Video Contrast Enhancement Module (VEM) automatically improves performance and accuracy in low contrast conditions.  This capability addresses a limitation in off-the-shelf CCD sensors which do not perform well in low contrast conditions.  It is especially useful in applications such as outdoor/defense (where environmental issues present challenges, particularly in long-range observation) and metrology/inspection (where low-contrast materials impede accuracy).

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Topics: Image Quality Improvements