Choosing the right digital camera

01 October 2007

A programmable camera may be the solution for complex image processing requirements that vary over time.

Most machine vision systems employ digital cameras, which use high-speed, charge-coupled devices (CCDs) as the image sensors. A CCD consists of an array of square photosensitive cells that convert
incoming photons to electrons and accumulate the resulting charge. Cells are wired in series, forming rows and columns, with each cell representing one picture element, or pixel.

During image readout, control lines in the CCD cause cells to transfer their charge to an adjacent cell in a row or column. Reading an image from a digital camera thus consists of many repeated row and column transfers that ultimately move cell contents past a charge sensor and digitiser to produce the camera output one pixel at a time.

Resolution vs. speed
One of a digital camera's primary parameters is its resolution, which has two components: the number of sensing elements (pixels) in the CCD array, and the size of each sensing element. Pixel counts can range from a few hundred thousand to many millions. Element sizes typically run from 5 to 12um on each edge.

A second key parameter is frame rate, or the speed with which the camera can deliver successive images. Because rowand- column readout limits speed, the pixel count and frame rate of a camera are intertwined: the more pixels a camera offers, the slower its frame rate. The rule is not hard-and-fast, however. A finer-geometry semiconductor process usually allows faster shift rates, so two cameras of the same pixel count could have significantly different frame rates if they use CCDs made with different processes.

Also, camera sensors may be designed to break the image into sections for simultaneous readout through
multiple ports. Breaking the image into four equal sections, for example, can speed the image readout by a
factor of four. It is also possible under software control to read out only an 'area of interest' in the image rather than the full sensor array, reducing the transfer time.

While resolution and frame rate are the camera parameters developers consider most often, several others merit investigation. One is the dynamic range, or number of bits per pixel. This parameter affects the memory size needed in the frame grabber as well as the arithmetic precision needed in the image processor. It also has an impact on the sensor's exposure latitude. Cameras with a few bits per pixel will support more restricted lighting conditions than a camera offering more bits.

A sensor's sensitivity also dictates the lighting conditions required for operation. Low light or the need to use
fast shutter speeds to eliminate motion related image blurring require a more sensitive camera. The camera's wavelength-dependent sensitivity may also be important. Depending on the application, infrared, ultraviolet, or even x-ray lighting may be needed, and the camera's wavelength sensitivity should match. Finally, a camera's ability to produce colour or monochrome images can be important.

These various parameters all interact to dictate a camera's cost. Typically, larger pixel-count cameras are more expensive. Similarly, faster frame rates for a given resolution also tend to boost camera cost. Trying to simultaneously achieve high frame rates and high resolution usually requires cameras with
multi-port readouts, which add cost and complexity.

Varying vision requirements
The right set of camera parameters for a given application depends on what the machine vision system is trying to achieve. Three common applications are visual inspection, contactless measurement, and identification and orientation of objects. Each has different vision requirements.

Inspection systems typically take an image and compare it to a template or 'knowngood' image to identify variations. Here, a high-quality image is often required for the image processor to make reliable comparisons. This means that the camera must offer high resolution and many bits per pixel. Colour capability may also be required.

Contactless measurement systems take pictures of objects, then count the number of pixels the object occupies, translating that count into a dimensional value. High resolution may be required in such systems, but bits-per-pixel may not need to be as high. Often, the image processor extracts only edges or outlines from the image, so wide dynamic ranges and colour typically are not needed.

Object identification and orientation applications have varying requirements. In many cases, the image processing system seeks to identify reference marks called fiducials in the image. The resolution required depends on the size of these marks relative to the overall image size. Identification applications
may also need colour capability.

Matching the application
Matching the camera to the application depends on performance as well as function. In an inspection application, for instance, the image area to inspect and the size of defects to be detected set the camera's resolution requirement. Finding small defects in large objects requires high resolution. One such system, used to rapidly inspect glass panels of highdefinition plasma televisions, looks for defects as small as 5¦Ìm on a panel 2.5 m wide. This system requires a dozen 11 megapixel cameras to image the entire sheet in one frame! A system for inspecting the screw threads on bottle tops, on the other hand, can work with much lower resolution, as defects must be much more substantial to compromise the bottle.

Measurement systems similarly depend on the size of the object involved and the precision needed to
establish the resolution requirement. A system measuring threads on a 10-mm- long machine with 1μm precision will require an image with at least 10k pixels in a line. If measuring the length with millimeter precision, however, much lower resolution can be tolerated.

Identification-system requirements can vary widely, depending on the nature of the matching template. A system to verify that pills being loaded into bottles are the right type (a safety feature in pharmaceutical manufacturing) may need to identify general shape, end cap colour, and visible markings at a fairly modest resolution. A system for automated assembly of circuit boards, on the other hand, may need very high
resolution. The system needs to measure positions of fiducial marks on boards in an assembly frame with high accuracy to control movement of componentplacement arms.

Frame rate sets throughput
In all these systems, the camera frame rate establishes system throughput. The higher the frame rate, the more inspections, measurements, or identifications the system can accomplish in a given time. Because throughput affects manufacturing cost, the tendency is to choose the fastest camera available.

The camera is not the only system element to be considered, however. Frame grabber and image processor speeds also may create limits. For instance, if image processing requirements are complex, a simple embedded processor may be unable to complete them as fast as the camera can supply frames. Thus, high throughput increases camera and other system costs.

Similarly, resolution requirements affect costs beyond the camera. Optics needed for larger image areas and finer details are more expensive. In addition, the optical design becomes more critical as better images are needed. Stray light in the wrong place can easily compromise system accuracy.

The tradeoffs
Resolution and frame rate thus have compound effects on system costs, so the benefits of machine vision systems in manufacturing must be evaluated carefully. Early detection of errors saves wasted effort and materials, but that savings must offset the cost of a vision system with the required throughput to be practical. Developers will need to determine the tradeoffs between vision system performance, system throughput, and cost savings to arrive at the right combination for their machine-vision systems.

Unfortunately for many installations, machine vision resolution and throughput requirements may vary over
time. For instance, changing product dimensions or production line reconfigurations may force replacement of machine vision cameras if they cannot match the new requirements. One way to avoid such replacements is to use a programmable camera in the first place. Programmable cameras allow users to change effective resolution and frame rates under software control so they can be matched to the application without an equipment change.

The interplay of performance parameters with system costs makes the evaluation of cameras for control
applications a challenging exercise. Programmable cameras can add flexibility to the solution, but they are
not a substitute for sound engineering. Developers need to understand application needs in detail, along with the benefits a machinevision system will offer, to determine the optimum combination of camera
parameters.

Petko Dinev is president of Imperx, www.imperx.com

Programmable cameras
Imperx’s large format 16 megapixel, thermoelectrically cooled digital camera uses a CCD that delivers three
frames per second at full 4872 x 3248 resolution. The camera offers fully programmable resolution, frame rate, and exposure control, allowing users to tailor its operation to the application’s needs. It is available in
either monochrome or colour configurations.

The camera’s image processing system is based on a 2 million gate FPGA and a 32-bit RISC processor.
Under control of its on-board intelligence, the camera can dynamically zoom from low-resolution at video frame rate (29 fps) to full resolution at 3 fps.

The Peltier-effect thermoelectric cooling actively controls the temperature of the camera’s extremely large CCD at a 20ºC. This stabilises the device’s sensitivity, dark current, and noise for applications where these
Programmable cameras Programmable cameras can add flexibility to the solution, but they are not a substitute for sound engineering. parameters are limiting factors.

Users can program the dynamic range by selecting from an 8, 10, or 12-bit output, and apply a number of other programmable functions, including frame rate, shutter, long integration, strobe output, gain and offset,
AOI (area of interest), external trigger, dynamic S/N correction, temperature monitor and alarm. Users can
field-upgrade the cameras’ software and firmware.

Control of the camera is accomplished via a serial port. The CameraLink® interface is used for the image data and there is an optional Gigabit Ethernet connection for both control and data. Electronic shutter control offers features such as pre-exposure and double exposure and speeds as fast as 1/12000 of a second. The shutters can be triggered under software control or use external trigger signals in addition to providing programmed exposure times. Automatic iris control is optionally available.



Related Articles...

Print this page | E-mail this page