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The most important considerations when implementing machine vision system illumination are illumination type, lighting geometry, color and wavelength (as they can significantly improve the visibility of certain objects), and camera compatibility. There can also be differences in lens structure and material that can impact image quality, as seen in KEYENCE's high-resolution lens CA-LH16 and standard lens CV-L16. This can affect the amount of contrast in captured images and general image resolution.

Reference What is a complementary color? A complementary color is the opposite color in the hue circle. When a light of the complementary color is applied to an object, the object will appear nearly black.

Since a metal surface reflects light easily and the inscription does not, the optimum method is to use specular reflection to enhance the difference between the surface and inscription.

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Backlighting projects even illumination from behind the observed target to highlight its silhouette. This type of lighting is mostly used for presence/absence detection, detection of holes and gaps, and measurements of target outline shape. However, this type of lighting isn’t best suited for the detection of surface details.

Machine vision lighting helps optimize the visibility of objects that are viewed and captured by cameras, enabling more precise image capture for analysis. It often enhances contrast, reduces shadows and reflections, highlights specific features, and enhances the effectiveness of image processing.

Understand the essentials of machine vision lighting selection and illumination techniques to improve accuracy and efficiency in industrial applications.

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Image processing is the process of detecting changes in pixel density data through calculation. As such, stable detection requires projection of a clear image. The lighting selection plays an important role in determining the performance of image processing–based inspection. This section introduces the basic knowledge required for selecting the correct lighting.

After you choose the lighting method, select the type of light based on the detection purpose, background, and surrounding environment. Basic selections are: coaxial illumination, ring illumination, or bar lights for specular reflection; low angle lights, ring illumination, or bar lights for diffuse reflection; and area illumination or bar lights for backlighting. Ring illumination and bar lights are generally used in particular because they can be used for various purposes by adjusting the installation distance.

Yes, there are specific considerations when choosing machine vision lighting for specific applications, and they mostly relate to object characteristics, such as color, size, and surface properties. However, it also depends on the features that need highlighting.

Lights of different wavelengths appear as different colors. The wavelength determines the characteristics of a particular color such as being transmitted easily (red light - long wavelength) or being scattered easily (blue light -short wavelength).

Even when no difference can be detected with reflected light, applying transmitted light from behind the target will show foreign matter as a black silhouette.

Backlight projects illumination from behind the object, creating a silhouette. Depending on the light source, this type of machine vision lighting can also be used to measure the dimensions of a particular object precisely or detect its presence/absence. Illumination selection is crucial in machine vision as it affects the accuracy and reliability of a vision system. For instance, ring illumination versus dome illumination for printed images on aluminum.

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It is necessary to bring out the contrast between the surface of the chip and the print by eliminating the reflection from the transparent film (halation).

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Machine vision lighting follows machine vision systems across innumerable applications within the industrial setting. This includes automated inspection and quality control during manufacturing processes, electronic assemblies, and food and beverage packaging and labeling. Uniform illumination also helps robots identify different items for pick-and-place applications and capture clear images on fast-moving conveyors in the packaging and logistics industries. Machine vision lighting is also used to detect whether the pills are the correct size, shape, and even color before they’re packed and shipped to the local pharmacy.

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Understanding focal length is key to understanding how your camera works. The focal length of a lens determines what your camera can focus on, and how your images are going to turn out. From selecting the right lens, to getting those picture-perfect shots, read on to learn more about focal length and how it impacts photography.

This guide is a compilation of trivia pertaining to vision systems. Figures are used to provide easy-to-understand explanations of principles and characteristics for items ranging from lenses, image capturing, lighting, and color to communication and preprocessing. This guide is a must-read for anyone wanting to learn all about vision systems.

It is necessary to bring out the contrast between the target surface and the foreign matter, which is difficult to recognize because of the subtle difference in color.

The last step is to determine the color of illumination according to the target and background. When a color camera is used, the normal selection is white. When a monochrome camera is used, the following knowledge is required.

The applications of some vision system lighting techniques require a special kind of light and geometry or different placement of the camera relative to the observed object, while other applications don’t. Whatever the case might be, most lighting manufacturers offer lights with various combinations of illumination techniques for vision systems available within a single product. This allows for greater flexibility and reduction in potential costs associated with lighting for different inspection methods.

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Also known as co-axial lighting- is a machine vision lighting technique that transmits light perpendicular to the target. All surfaces hit at an angle to the camera will be dark and thus more visible. It’s an exceptionally useful technique for detecting flaws on flat, shiny surfaces.

The following is an image comparison of print on a chip in carrier tape taken through a transparent film. The contrast is higher with red illumination than with blue illumination, because of its higher transmittance (lower scattering rate).

Bar lighting illuminates the target along its edge or provides uniform lighting along a localized area. It can be combined with other bar lights to illuminate the target from all directions. This type of light can enhance or reduce specular reflection, depending on light and camera placement and angle. It’s typically used to add contrast to matte surfaces and to highlight surface features of matte objects.

Light selection determines the conditions of captured images, which is most important for image processing. Instead of trying every light without consideration, you can select the right one efficiently by following the procedure below:

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Dome lighting provides uniform illumination from various angles, resulting in the absence of glare. It’s perfect for inspecting shiny, bumpy, or cured surfaces, but it needs to be close to the target to be effective.

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KEYENCE supports customers from the selection process to line operations with on-site operating instructions and after-sales support.

The first step of light selection is to select the lighting method, specular reflection, diffuse reflection, or backlighting, according to the shape of the target and the inspection purpose. Then, select the size and color of light that allows you to capture an optimum image for processing.

A red candy wrapper is in a cardboard box. The following is a comparison of the contrast when LED illumination is used to detect the presence or absence of the candy.

This type of machine vision lighting provides light in a way that exposes surface defects, such as scratches, imprints, notches, and all imperfections, which reflect the light back to the machine vision system camera.

The next volume will cover “the effects of color cameras and image enhancement”. It is an important factor for processing the image to the optimum application such as appearance inspection and position detection. The next guide will outline points for selecting the optimum color extraction and image enhancement.