When machine vision first came onto the scene in the 1970s and 80s, the technology was generally over-promised and under-delivered. Systems were very costly — running from $15,000 and up — and their operation and maintenance required highly trained technical staff. For these reasons, machine vision was initially used only for applications in which production mistakes were particularly costly. Now, many more industrial manufacturers are using machine vision to ensure product quality, traceability, and production efficiency. Why?

While vision systems once required highly trained technical operators, the interfaces have evolved to be user-friendlier. In fact, ease-of-use is undergoing the most dramatic advances.

Today, machine vision is more affordable, user-friendly and offers significantly more features and functionality. Plus, traditional vision systems (used in applications we'll detail) consist of separate hardware and software that often require significant programming time and the use of an auxiliary computer. However, some newer vision now combines multiple elements in single units, with programming performed through an integrated touchscreen, eliminating the need for a PC or other programming device.

Vision uses

Photoelectric and ultrasonic sensors are suitable for applications in which one specific area on the same type of part must be examined. In contrast, machine vision analyzes and interprets data from an entire image scene, rather than a single point. This capability allows for inspection of larger object areas, multiple part features, and features that differ from the surrounding area in more than one way — in texture, color, and height, for example.

Vision sensors can also be programmed to distinguish bad parts from good; inspect multiple parts with one feature of interest; and make multiple inspections with different criteria, when multiple parts travel on the same line.

Functionality

Vision sensors perform inspections in three basic steps. First, its camera acquires an image of the part. Next, a processor analyzes this image and then determines if the inspection passes or fails — and reports results to the manufacturing line.

Capabilities are determined by hardware (including camera and controller) and software, consisting of controls, graphical user interface, and image algorithms. While camera resolutions and image quality have improved greatly over the past years, improved capabilities and accuracy are largely due to improved processors and memory density. The availability of increased storage space and speed allow execution of more complex algorithms in a timely fashion.

Vision-sensor tools allow differentiation of characteristics that identify good and bad parts. One caveat: Algorithms and processor (even the fastest) cannot compensate for poor images: Increasing the contrast between a good and bad part does more for application robustness than most technology improvements.

Application examples

Typically, vision sensors are loaded with application-specific tool sets. For instance:

• A locate tool is an edge-based tool that finds absolute or relative target position in an image by finding a particular edge. This tool can be used to quickly locate the position of a label on a package, for example.

• To match letters and numbers on a label, a pattern-find tool finds the absolute position and rotation of a taught pattern within the search region of interest with normalized gray scale correlation or geometric-based pattern matching techniques. The template pattern information is stored in memory and all potential matches are compared to it.