What is computer vision?
Computer vision or computer vision is the discipline (branch of Artificial Intelligence) that studies algorithms and techniques to enable computers to reproduce functions and processes of the human visual apparatus in order to extract useful information for processing.
Thanks to the combination of technologies and methods, it is possible to perform automatic image analysis in various applications in industry to solve specific problems: identification, measurement, defect recognition, robot guidance, robot navigation, etc..
The development of increasingly advanced machine learning and deep learning techniques has made it possible to achieve performance comparable to human performance or better in fact superior in detecting and reacting quickly to visual input.
How do machine vision systems work?
The investigations on an image that computer vision can perform are more or less in-depth depending on the techniques used, the type of image and the type of request made.
Computer vision works as follows
- Image acquisition
Images, even large ones, can be acquired in real time via video, photos or 3D technology, for analysis purposes. Neural networks for computer vision work by distinguishing the many elements that make up an image, identify the edges and then model the sub-components. Using filtering and a series of actions through the deep layers of the network, they put together all the elements that make up the image. - Image processing
Machine and deep learning models automate much of this process, after being trained by loading thousands of labelled or pre-identified images, they generate an algorithm capable of processing them independently. - Image interpretation
The final stage is interpretation, which consists of identifying or classifying the image according to the required application.
The main investigations therefore may concern:
Image Classification: analysis of image content and attribution of a label;
Object Detection: identification of one or more entities within an image;
Image Segmentation: subdivision of the image into sections;
Face Recognition: recognition of people’s faces;
Action Recognition: identification of one or more entities and their relationship in time and space, in order to identify and describe specific actions;
Visual Relationship Detection: understanding the relationship between objects in an image;
Emotion Recognition: detecting the sentiment of an image;
Image Editing: editing an image.
The most relevant difficulties in these investigations concern the possible associations or ambiguities that the algorithm might make/assess. Therefore, it is very important to develop a large dataset for training the algorithm. Precisely because the algorithm developed must also include the image when there are transformations such as changes in light, deformation of the object or changes in scale. A very real case when thought of within a production plant.
In the industrial field, vision systems find different applications thanks to the possibility of being integrated directly on production lines and in factory environments. Their application is also increasing rapidly because they are a fundamental element in digital transformation and Industry 4.0.
At Kablator, the KabVision Business Unit is ready for any machine vision challenge!
Machine vision systems in industry
There is no longer any doubt about the validity of using vision systems for factory automation to optimise production activities. The advantages of machine vision applied to the manufacturing industry can be summarised as follows:
- considerable reduction in development time;
- maximum possible precision in applications;
- improved product quality and system efficiency;
- reduction in downtime;
- reduction in labour costs;
- safety in the working environment;
- possibility for people to concentrate on higher value-added operations.
The benefit derived from all the above is that of increased productivity of production lines.
The main applications and automatic inspections in industry are:
Quality control: detect defects, dimensional variations, imperfections, conformity of parts, suitability of assemblies, quality of surfaces and profiles, colours very accurately and quickly compared to human inspection.
Code and label reading: label reading, print verification and control of part position and orientation, content or fill level analysis.
Critical processes: through real time analysis of images, machines can make quick decisions.
Robot guidance: automated application for picking tasks, inspection and selection of 2d and 3d objects or for checks on non-standard machining.
Predictive forecasting: constant monitoring of equipment and machines, fault prediction and maintenance interventions.
Environmental safety: identification of hazardous situations to ensure compliance with safety regulations.
Companies that adopt machine vision systems enjoy a significant competitive advantage by improving their adaptability and agility in a very complex industrial environment.
Our KabVision business unit was created precisely to develop this competitive advantage for companies that rely on our consultancy to solve problems within their production systems.
For KabVision technology consulting:
+39 3313466711- info@kablator.com
