Illumination techniques for industrial image processing
Image processing systems generally comprise a camera or sensor and a processing unit (usually, but not exclusively a computer equipped with a frame grabber and image analysis software). Smart cameras are often also regarded as image processing systems. But alongside these obvious components, the illumination system plays a crucial role. Strictly speaking, image processing tools do not inspect the object itself, but instead examine the visual image of the object as captured by the system, and stable, reproducible illumination conditions must be in place in to ensure constant image quality of identical objects or identical conditions. Therefore, fluctuations in illumination must be avoided if strict quality criteria are to be applied to the inspection of objects.
Only when it is possible to view the specific features or faults with sufficient contrast is it possible to evaluate them using image processing software. This is generally achieved by illuminating the object using a light source, although fluorescent objects are an exception to this rule. The principle of “illuminating the object under inspection may seem banal, but experience shows that one of the main difficulties in image processing is to make faults in the object visible to the camera at all.
Applications that demand carefully chosen illumination might include a transparent glass bottle on which the embossed lettering at the bottom must be read. In other words, the object under inspection and the features to be inspected are of the same material, and to make things worse, the material is also transparent! By contrast, a scratch on a metallic surface generally requires only the recognition of the surface feature as distinct from the surface itself. Here again, we have an inspection situation in which faults must be identified despite the material being identical. The same also applies to embossing and deformations in materials.
The crucial role here is always the illumination and its interaction with the 3 main considerations, namely; the illumination, the object and the camera (see Figure 1).
It is often only by the skilful exploitation of the special characteristics of a particular light source, lighting geometry, object characteristics and the camera which allows difficult applications to be solved. The key characteristics are as follows:
- Light: Wavelength (colour), direct/diffuse illumination, non-polarised/polarised, angle of incidence
- Object: Material, surface, geometry, colour
- Camera: Sensitivity, resolution, monochrome/colour, CCD/CMOS
Since the physical characteristics of the object under inspection can only be influenced in exceptional cases (e.g. by colouring components or using UV- sensitive pigment additives), the object itself will usually determine the choice of illumination and camera type. The lens is determined by the connector thread of the camera and the working distance from the object. The data format and data rate supported by the camera also determine the frame grabber used.
Various light sources
The light employed in image processing applications is generated in a wide variety of different ways. Depending on the task, required light intensity, object size and the space available for installation, the following are generally used:
For several years now, [LED illumination(glossary/121) has taken an increasing share of the market compared to other light sources. This trend is explained by the large number of benefits offered by LED technology. These benefits include a considerably longer service life of up to 50,000 hours, extremely simple control facilities, the mechanical resilience and small physical size of the units, design flexibility, lower operating costs and excellent value for money. As far as ring lights and similar illumination shapes are concerned, the LED has already become well established as the light source of choice.
Although traditionally the domain of halogen or metal-halide-based cold light sources, fibre-optic illumination now appears to be a segment in which LEDs are rapidly gaining ground. The Swiss company FiberOptic (aka Volpi) is one of the best known manufacturers of cold light sources. Recently, they introduced a cold light illumination unit in which LEDs are used to generate the light in place of metal halide lamps (see Figure 4). This innovative LED light source combines the benefits of the LED with those of fibre optic illumination units.
Laser illumination has a special role to play in image processing. Using a laser-generated light structure and a camera plus downstream image analysis makes it possible to measure differences in height and profiles, if the angle between the camera and the object is known (see Figure 5).
The combination of lasers with image processing opens up possibilities for a number of interesting applications in a wide range of different sectors (see Figure 6 for an example).
Illumination units using fluorescent light or based on halogen lamps are only used relatively rarely in the world of image processing. They only usually make sense for use in special applications, so we shall not discuss them any further here.
The role of colour
In everyday life, people generally see objects that are illuminated with “white light (sunlight, artificial lights). White light is also regularly used for illumination in image processing. Depending on the application, however, different coloured light is also used. Red is regularly used. The reason for this is illustrated by the following example of a label on a drinks bottle: The human eye sees a coloured label with dark blue and red lettering (see Figure 7).
For the monochrome cameras which are most frequently used in image processing, the label looks like a photocopy: Red and blue have both become grey and the rest is light grey or white (see Figure 8).
If this label is now illuminated with red light, the red, white and grey elements appear red to a colour camera and blue and black elements appear black or grey (Figure 9). The reason for this is that the monochromatic red light of the LEDs is reflected by the red, white and grey elements but not by the blue and black elements.
Figure 7: Label for the human eye
Figure 8: Label for the monochrome cameras
Figure 9: Label with red light
Figure 10: Label with with red illumination and a monochrome camera
Thus, if the user in this example only wishes to check that the “Pepsi“ lettering has been printed correctly, a colour camera and red illumination would be an eminently suitable choice for masking out those elements which do not need to be inspected. Interestingly, however, the same information can be extracted with red illumination and a monochrome camera (which is generally less expensive). This is illustrated in Figure 10.
The angle of incidence of light on the object also influences the result. There are several different techniques, such as front illumination or backlighting, direct or diffuse illumination, bright-field or dark-field illumination. Figures 11 through 15 illustrate how different an object may appear depending how the illumination is organised.
Direct front illumination (a ring light illuminates the objects directly, more or less parallel to the optical axis of the camera). The image appears non-uniform and mottled. . (Figure 11)
Diffuse bright-field illumination: The image appears more uniform. There is a strong contrast between the object and background, but the reflective surface of the connector 'floods' the camera, i.e. the camera is "dazzled" and no longer detects some details. Furthermore, shadows are formed over the upper part of the connector. (Figure 12)
Diffuse dark-field illumination: Light with an oblique angle of incidence from a ring light with an angle between the front illumination unit and the object. Further detail can be seen on the connector and no shadows are formed. (Figure 13)
Figure 11: Direct front illumination
Figure 12: Diffuse bright-field illumination
Figure 13: Diffuse dark-field illumination
Dark-field illumination: Shallow angle of incidence of the light on the object plane. The top edges of the pins, the connector and the holes appear as bright circles and can thus be easily identified busing image analysis software. The missing pin (no bright circle) and the bent pin (incorrect position) are more easily visible when compared to front illumination. (Figure 14)
Backlighting: Light is aimed towards the camera from the rear of the object. The light only penetrates where there is nothing to obstruct it. This allows the drill holes on each side of the connector to be measured accurately. An easily detected bright spot appears in place of the missing pin. (Figure 15)
Figure 14: Dark-field illumination
Figure 15: Backlighting
So five different illumination techniques deliver five completely different results!
Ask the experts!
Even this brief introduction to industrial illumination techniques is sufficient to show that it is only possible to select the ideal illumination after the task has been precisely defined, which often demands considerable experience. But users have an easier option than a time-consuming process of trial and error:
STEMMER IMAGING is Europe’s largest technology and service provider for the image processing industry, stocking among other things a wide range of several hundred universal and specialist illumination units from the world’s leading manufacturers such as CCS and Volpi. Our many years of experience mean that we shall certainly be able to find the ideal illumination solution for any industrial image processing task – including yours.
- Learn more about illumination: Intelligent lighting ... in 3 parts