Image Recognition in Industrial Automation - Digimax

The important evolution of artificial intelligence opens up interesting development opportunities for industries and businesses. More and more companies are using computer vision systems to improve processes and increase productivity, especially through image recognition technologies.

Computer vision, or artificial vision, is what allows a machine to process a static visual input, such as an image file, or a dynamic one, such as a video recording, to understand its content.

One of the most interesting applications of machine vision is image recognition: the technology capable of identifying objects and elements within an image, analyzing them and drawing conclusions, in order to automate a specific activity.

What is Image Recognition?

An artificial intelligence system is capable of processing visual information thanks to computer vision technologies, a system capable of identifying objects or categorizing figures based on their content instead carries out an additional process, image recognition.

Photo or video recognition can be performed with varying degrees of accuracy, depending on the type of information requested or the type of embedded board or industrial PC used within the project. For example, an image recognition algorithm may be able to detect a specific item or to assign a general category.

It is therefore good to distinguish the different image recognition models:

• Image Classification: the algorithm acquires the image and attributes a "class" label, i.e. a certain category, estimating probability, loss, or accuracy values;
• Object Localization: the algorithm identifies the presence of an object in the image and outlines it in a bounding box, returning its position in height and width values;
• Object Detection: the algorithm combines image classification and object localization, outlining multiple bounding boxes combined with its class label;
• Image Segmentation: the algorithm detects and signals the presence of an object through an extremely precise pixel mask, generated for each object in the image.

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How does image recognition work?

Image recognition technology is based on Deep Learning, a branch within AI and Machine Learning: a set of machine learning techniques based on artificial neural networks.

Logically, unlike human neural networks, artificial neural networks are developed on specific software with different degrees of structural complexity that regulate algorithms, mathematical functions, and input-output systems to process the individual pixels of an image and associate a concept.

In order for the neural networks to recognize one or more concepts in the image, it is necessary to feed them with a first set of pre-compiled visual data: these will be the learning basis for "teaching" the neural networks to recognize similar images autonomously and draw conclusions from them. conclusions.

What can image recognition do?

With an image recognition system, it is possible to automate business processes, reduce management costs and improve productivity. In fact, from the moment a machine recognizes a given element in the image, it can be programmed to perform a certain action. Numerous applications have already been implemented on a large scale in various sectors and industries:

Video surveillance: The recognition of people, machines, and objects can contribute to security and access control, for example for the occupation of buildings or rooms, the regulation of traffic of people or vehicles, and the surveillance of areas subject to risks or restrictions.

Automotive: the innovative projects of autonomous driving of vehicles use image recognition systems for people, objects, other vehicles, and static or moving elements with different speeds, in order to recognize their characteristics and to predict their displacement in space.

Hospital: artificial intelligence can effectively contribute to the detection of anomalies or deviations from standard conditions, signaling radiographic and ultrasound images, and analyzes of various kinds as potential cases for clinical and diagnostic investigation.

Retail and large-scale distribution: in the field of visual merchandising, an image recognition system analyzes consumers to observe their characteristics and where they pay more attention, obtaining useful information for the targeted display of goods or the selection of products to offer.

Industrial Production: the artificial intelligence of image recognition is used for the automation of quality control of all kinds of products, immediately recognizing non-standard or defective items by analyzing their shapes, appearance, color, or other parameters.

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Digimax and image recognition in the industry

In image recognition projects applied to industry, Digimax uses a wide range of industrial cameras e embedded pcs to develop complete artificial vision systems, capable of supporting the detection of photos and videos and automating the most varied business processes.

Machine Vision technologies and Artificial Intelligence offered by Digimax guarantee an extremely precise recognition of images, both static and in movement, classifying them into different elements such as people, objects, texts and detecting their characteristics, anomalies, and metadata.

Digimax industrial solutions for Computer Vision and image recognition are suitable for:

• Automatic detections of static or moving objects, features, and placements
• Analysis and identification of malfunctions, anomalies, or variations from the standard
• Automated visual checks of product quality and production process
• Increase workplace safety by ensuring real-time video surveillance
• Enhance the value of images in the most varied sectors, from retail to medical

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