Lighting is a critical, yet often misunderstood factor. Improper lighting can wash out desired image information and highlight unnecessary features.

Cleanliness varies in each environment. A case in point is an industrial environment where dirt and dust collect on lens optics and lighting sources, lowering illumination levels and reducing contrast. Machine vision components especially actuators in moving fixtures may introduce their own dust and dirt into semiconductor fabrication environments, potentially ruining thousands of chips.

Environmental concerns such as temperature, humidity, vibration, and ambient illumination can not only harm equipment, but also limit system capabilities. For instance, a machine vision system cannot measure a part s width to 0.02 mm if the part is vibrating with amplitude of 0.2 mm.When developing a machine vision system, the first step is deciding whether to build it in-house or use a qualified integrator. Third-party integrators are suggested, as they have extensive technical expertise and can recommend component suppliers. Once this is decided, engineers can begin choosing machine vision components.

Considerations

When developing a machine vision system, the first step is deciding whether to build it in-house or use a qualified integrator. Third-party integrators are suggested, as they have extensive technical expertise and can recommend component suppliers. Once this is decided, engineers can begin choosing machine vision components.

Camera selection is an important choice, and a significant specification is sensor size. Sensors were once available in 1/4, 1/3, and 1/2-in. sizes only, but now come in sizes up to 90 mm. Larger sizes offer higher resolution, but require larger lenses and increase the entire system s space requirement. Dividing sensor size by image (lens-to-sensor) distance gives the camera s angular field of view (FOV) in radians. Then, dividing an object s size or scene by this angle determines the distance from the object to the lens.

In most cases, engineers match a camera s resolution to a task s critical dimensions. It is important not to confuse image resolution with a motion control system s resolution. For example, semiconductor processing equipment reaches submicron motion control resolution, which visible light optics cannot physically achieve and which is irrelevant to a vision system reading wafer ID codes.

Next, designers must consider the lens and its focal length f. Required focal length depends on required FOV size F, sensor size S, and the camera s image distance v: f = (Fv) / (S+F).

Sufficient illumination and the amount of time a shutter remains open determine the size of a lens opening, or aperture. The larger an aperture and the brighter the illumination, the faster a camera captures images. Lens manufacturers specify apertures as the ratio of focal length to lens opening, often called the f number. Relatively large lenses have f numbers below 4; those above 5.6 are called slow because their small apertures take significant time gathering enough light to form an image with adequate contrast. Generally, engineers should employ the fastest (lowest) f number possible.

In addition, a lens must mate with a camera. Therefore, lens mounting should form a light-tight seal around the lens, holding it rigidly against the camera s body. Many lens-mount standards borrowed from photographic or video-surveillance applications work well for small-size (1/2 in. or less) sensors. For 35 mm or larger sensors, mounting becomes problematic and may require a custom design.

When choosing light sources, designers strive for fixed illumination levels that will produce an evenly lit scene. Levels that change frequently are often due to a flickering or aging source. Flicker creates rapid changes that a person can t see, but that foil short-time exposures. Aging causes slow decreases or increases in overall output, which washes out detail. As a result, machine vision integrators usually choose LED light sources for their stability and reliability.

A scene s size and geometry determine illumination. When illuminating large scenes, one might consider a vast array of bright lights strategically arranged to fill the space an object moves through. The two basic geometries are a flat even area source common when silhouetting objects and ring lights that fit around a lens and illuminate an object s visible face.

An object s surface morphology, color, and finish also affect light-source selection. Objects with a complex morphology, such as machine parts, create shadows that change as they move. Shiny surfaces are especially difficult, as they appear dark from most angles, but flare brightly when reflecting a light source directly into the lens.

Self-operating vehicles A team from Stanford University adopted machine vision to pilot this driverless vehicle to victory in the 2005 DARPA Grand Challenge race across the Mojave Desert. Photo courtesy Stanford University. One demonstration of machine vision s flexibility is the 2005 DARPA Grand Challenge, in which driverless vehicles raced across 132 miles of Mojave Desert from Los Angeles, to Las Vegas. Of the 23 starters, five finished in less than ten hours and the winner included machine vision as their primary sensor. Sensors distinguished hazards, such as rocks, ditches, and animals that couldn t be sensed otherwise and also helped the vehicles recognize and follow the correct driving path.

For more information, contact Edmund Optics at (800) 363-1992, visit edmundoptics.com, or write the editor at ctelling@penton.com