Contour detection is an important tool for 2D image processing. The edges as well as the transitions from foreground to background are detected and a contour is calculated from the information. The special feature of contour detection is that it also works reliably with interference caused by extraneous light, as the extraneous light usually hits the entire object. The relative difference between foreground and background shifts, but the contour is still detected with equal certainty. Object inspection is then performed by matching a reference contour with the current object.
The method is mainly used in pattern and shape detection as well as object recognition, as typically applied in punching, milling, turning or assembly. Contour detection is used for quality assurance in these areas.
Blob analysis is an important image processing method in which image features are selected and analysed over a group of similar neighbouring pixels.
The BLOB (invented word Binary Large Object) in this context stands for Binary-Logic Data Object, which loosely translates as a set of pixels with the same logical state. The selection of the neighbouring pixels is generally done by thresholding the grey-scale value. Conclusions can then be drawn about various characteristics from the analysis. A well-known function is, e.g., the pixel counter.
There are many different applications. For example, blob analysis can be used for monitoring completeness, detection of presence or thread detection as well as for counting and sorting objects.
The position tracking is done by means of an anchor contour that is found once in the image. Using this contour, search zones can track other models (for example, the search zone of a blob analysis) in position as well as orientation.
Graphical representation of a position tracking based on the example:
The O2D5 family from ifm uses a CMOS image processor with 1.2 MP (1280 x 960 pixels).
CMOS image processors are easier, faster and cheaper to manufacture, making them the most widely used on the market.
In order to maximise contrast for each pixel it is important to choose the right illumination. The O2D family is supplied with integrated high-intensity LED light sources in RGB-W (red, green, blue, white) and infrared.
Please note that the image sensor is not a colour sensor!
However, choosing a light source with a different colour can have a dramatic effect on the contrast of the image. The picture below shows crayons in daylight and, for comparison, illuminated by the different LEDs of the O2D5 sensor.
Light type | Please note: |
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Daylight (reference) |
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Red light |
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Green light |
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Blue light |
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White light |
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Infrared light |
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Due to reflections, it can be difficult to get sharp contours or areas on shiny objects. The O2D5 sensors with RGB-W light sources contain a polarisation filter that can be switched on or off to minimise the effect of reflections.