Main Features of Computer Vision

The fourth industrial revolution has undoubtedly brought great achievements in the field of productivity: improved product quality reduced costs, and even improved environmental conditions by reducing energy consumption, waste, etc. Especially worth highlighting is the role of artificial vision or computer vision, which is one of the most widely adopted technologies and produces results in the shortest time.

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Fundamentals of Computer Vision

Artificial vision is based on advanced technologies for digital transformation processes, highlighting primarily the Internet of Things (for capturing images) and deep learning (for processing said images and recognizing objects or patterns on them, which allows decision making).

Significant and very significant progress has been made over the past 20 years.  Moving from classic vision systems capable of reading predefined objects such as barcodes or knowing the presence or absence of a label, and even combined with optical character recognition techniques capable of reading texts.  This classic machine vision was based on the following algorithm:

Computer vision

But it is in recent years, thanks to the combination of these image capture methods along with the learning power of artificial intelligence algorithms and especially deep learning, that computer vision has made an exponential leap both in terms of its capabilities and the results obtained.

Artificial vision

Capturing and processing images is key, which tends to tailor it to the intended purpose.  It is for this reason that, in addition to using classic RGB cameras, we work with infrared, ultrasonic, and even spectral cameras, which allow us to detect elements that are invisible to the human eye or that color can hide.

Benefits and Applications of Computer Vision

The use of this technology brings significant improvements to the industry in which it is applied, such as performance optimization, increased quality control, cost reduction, standardization, etc. These improvements are related to their specific application, such as:

-Detect element positioning.  The ability to determine if an object such as a cap or other object is in the correct position to continue the assembly line, thus avoiding quality problems or even an uncontrolled stoppage of the process.

-Identification of unwanted objects.  It is possible to identify unwanted elements in the production chain, such as glass, screws, etc., which can cause a serious problem on the line.  Or that it is included in our final packaged product and therefore could cause a serious quality problem if not detected.

-Identification of aesthetic defects.  These systems can benefit from the knowledge of the operators based on the training provided during previous quality checks.  They can recognize defects that can be interpreted by operators, allowing standardization of criteria as well as a significant increase in productivity.

– In addition to aesthetic defects, these systems can detect metrological problems, determine whether there may be problems with fit in subsequent stages of assembly, or whether they meet the parameters requested by our end user.

-Associated with robotics.  Artificial vision is a lever of automation for manufacturing plants, as they are the eyes of robots.

-Control security measures.  In addition to the production line, artificial vision helps us to monitor the compliance of personnel and logistics systems with established safety measures.  They identify personnel or elements in restricted areas by controlling the safe distance between people.

As we can see, computer vision is a fundamental lever on our path to digital transformation.