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Camera features and functionalities

Camera manufacturers include a wide range of functions in their products to meet the increasing demands of the industrial market. Some of the key camera characteristics and common features are discussed in this section.

Image fidelity

Objective measurement of fidelity would include quantity of random noise, accuracy of colour reproduction and the MTF (Modulation Transfer Function) of the camera/lens set-up. In a true machine vision appli cation these should be all that matter. However, where humans are involved, there is also a subjective element and sometimes the application engineer perceives an optimised camera image as "looking worse" than a non-optimised image.

Exposure time

This is the amount of time that light is allowed to fall onto the sensor, namely the period when electrons are being gathered due to the photoelectric effect. Longer exposure times allow the sensor to gather more light, but this leads to more noise being generated on the sensor.

Standard vision cameras usually specify the maximum exposure time to avoid noise becoming an issue. Short exposure times are needed when imaging a fast moving scene to avoid exposure blur, typically the exposure time should be short enough so that the object moves by less than 1 pixel.

For example, an area needs to be imaged that measures 100 mm x 100 mm, the speed of the object is 100 mm/sec and the camera has a resolution of 1K x 1K pixels. Each pixel will be imaging an area of 0.1 mm, so in 1 second, the object will have moved by 1000 pixels which will require a camera capable of exposure times of 1/1000th second or faster to avoid motion blur. With an excessive exposure time the image will appear as out of focus image that can only be analysed with considerable effort.

Frame rate

A complete image from an area scan camera, or one that is built-up from the output of a line scan camera, is called a frame. The number of frames that can be output from the camera in a particular time is referred to as the frame rate (typically frames per second or fps). To calculate the frame rate required, the frequency with which the object to be viewed is changing has to be considered.

For example, consider a production line where objects are passing by at a rate of 20 units per second. This will require a camera capable of capturing 20 discrete frames per second