Industries are witnessing rapid growth of machine vision. This technology being a vital component of the industry’s modern automation solutions, they expect the market for 3-D machine vision to nearly double in the next six years. In the manufacturing context, two major factors contribute to this increase in adoption of the machine vision technology. The first is due to the industry facing acute labor shortage problems, and the second is the dramatic decrease in hardware costs.
Additionally, with an increase in technological performance, the industry needs machine vision systems to process ever-expanding amounts of information every second. Moreover, with the advent of machine learning and advanced artificial intelligence algorithms, data collected from machine vision systems are becoming more valuable. The industry is rightly realizing the power of machine vision.
So, what exactly is machine vision? What makes a robot see? A vision system typically is a conglomeration of many parts that include the camera, lighting sources, lenses, robotic components, a computer for processing, and application-specific software.
The camera forms the eye of the system. There are many types of cameras that the industry uses for machine vision. Each type of camera is specific for a particular application need. Also, an automation solution may have many cameras with different configurations.
For instance, a static camera typically remains in a fixed position in a scenario where speed is imperative. It might have a bird’s eye view of the scene below it. On the other hand, a robotic arm may mount a dynamic camera at its end, to take a closer look at a process, thereby picking out higher details.
One of the important aspects of the vision system is its computing power. In fact, this is the brain to help the eye understand what it is seeing. Traditional machine vision systems were rather limited in their computing powers. Modern machine vision systems that take advantage of machine learning algorithms require far greater computation resources. They also depend on software libraries for augmenting their computing capabilities.
Machine vision manufacturers design these capabilities specifically for application users. They design the software to provide advanced capabilities for machine vision systems. These advanced capabilities allow users to control the tasks for the machine vision, such that they can gain valuable insights from the visual feedback.
With the industry increasingly using vision for assembly lines, the concept of a vision-guided system replacing basic human capabilities is on the upswing in a wide range of processes and applications.
One of the major applications of machine vision is inspection. As components enter the assembly line, machine vision cameras give them a thorough inspection. They look for cracks, bends, shifts, misalignment, and similar defects, which, even if minor, may lead to a quality issue later. The machine vision compares the crack, and if larger than a specified size, rejects the component automatically.
In addition to mechanical defects, machine vision is capable of detecting color variations. For instance, a color camera can detect discoloration and thereby reject faulty units.
The camera can also read product labels, serial numbers, or barcodes. This allows the identification of specific units that need tracking.