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Machine vision lights are available in various form factors differentiated by lighting configuration, shape, and output intensity. These determine how the light projects onto the sample. Different levels of uniformity, degree of collimation, and structured light patterns can affect an image. The light intensity must also be sufficient to overcome any unwanted contributions from ambient light.
Wavelength
The wavelength of light used is another important consideration as ultraviolet (UV), visible, and infrared (IR, NIR, SWIR) wavelengths can produce different images.
Imaging
The resolution, spectral response, and sarating.of the
the final image. In addition, the lenses and apertures can affect both the amount and the spectral and spatial distribution of the light reaching the image sensor. The sensor must receive sufficient light from the inspected obiect to minimize the noise in an image.
There are many factors to evaluate for in lighting applications to optimize image quality, including:
The shape, size, material, color, texture/finish, etc. of the part to be inspected
What features must be detected?
Does the part appearance vary?
Is the workpiece moving during image acquisition, and if so, at what speed?
What is the desired camera exposure time (if known)?
How is the workpiece presented to the camera? (orientation, tolerance, etc.)?
What is the working distance and the size of the field of view?
Are there any environmental constraints (such as dust/dirt, heat, washdown, size, etc.)?
This evaluation process provides the framework to choose the best lighting solution for the particular application from the extensive range of commercially available machine vision lighting configurations.