The 3D scanner for used tires automates the data entry of key information, automatically measures the tread depth, identifies unacceptable wear, and classifies each tire according to configurable criteria. Discover how computer vision can automate inventory control and management.
Specialvideo proposes an incremental workflow to automate the quality control of finished fabrics with Artificial Intelligence.
The neural networks underlying Artificial Intelligence for computer vision must be trained with real images of the product to distinguish defective portions of finished fabrics in the continuous flow of compliant products.
It is true that AI is flexible and can give surprising results on similar products never seen before, but it is also true that the best performance is achieved by providing Artificial Intelligence with images acquired in the field of the same textile industry for which the system is intended.
Specialvideo has designed a progressive path for integrating AI into quality control for continuous textile production, which is structured in implementation and study phases:
Therefore, the first fabric inspection system installed in the factory has two purposes:
Solid colour inspection implements monochromatic processing capable of finding stains, holes and other alterations.
Each product non-conformity is stored in the digital defect map, the file that represents the reel by tracking the defective portions of the fabric and their position on the roll.
The same vision system is activated by the customer in colour image acquisition mode for AI training, in order to capture the portions of fabric with defects.
During these acquisition sessions, defects must be marked in advance with adhesive labels.
The vision system is capable of recording counts and statistics useful in the context of Industry 4.0.
To learn more about Specialvideo’s experience in the field of visual inspection with linear cameras, please read the case history of vision systems for PVC rolls.
Using Ultralytics’ YOLO models, Specialvideo has developed a reliable, high-precision quality control system for pizzas that identifies, counts, and verifies toppings on the fly.
Specialvideo develops high-precision robot guidance systems for the food industry to automate handling, coating, and finishing operations, through to food packaging.
For example, it has implemented solutions for quality control of cookies and crackers, integrating vision systems with robots to identify defects and manage product handling.
Just in the food industry, Specialvideo has extended the application of robot guidance to multi-robot lines for complex systems, improving the flexibility and efficiency of production processes.
Among the most recent applications, Specialvideo has developed 3D robot guidance for automatic ham greasing. The machine vision system is responsible for 3D reconstruction of the ham surface, identification of the part to be greased with AI, and generation of the spray path.
The featured photograph depicts the system in operation and participated in the “Frame the Innovation” Machine Vision photo contest.
Specialvideo developed the 3D vision system on board the machine dedicated to reading the DOT code on tires, in collaboration with Uteco Contec
The fully automatic 3D reading cabin detects the DOT code printed on the tire in any position, without manipulating the tire.
The code reading is based on deep learning with a hybrid solution that combines the strengths of neural networks with traditional algorithms: reliability, accuracy and generalization.
The system works at high speeds and without knowing tire diameters and heights in advance.
To learn about the system, we invite you to read the case history and contact us for more information.
Specialvideo presents a Deep Learning quality control for pizzas, that inspects the toppings by returning the count and extent of ingredients classified by type, as well as performing classic checks such as shape integrity, color conformity, and detection of possible blue pollutants.
The application made for pizzas is suitable for other food products that have the ingredients to be checked visibly arranged, e.g., ready-made salad and pasta dishes.
To learn about the system, we invite you to read the case history and contact us for more information.
In the field of industrial quality control, ultra-high resolution images are characteristics of spot checks carried out with optical instruments by specialized operators.
Specialvideo offers the automation of visual inspection at very high resolutions, through::
The total size of the product and the cycle time, selected by the customer, will be the basis of the design of the scanner, which can be composed of a group of several cameras, which can be matrix o linear cameras depending on the type of inspection.
The following image, deliberately enlarged to allow to see the resolution of 3 microns per pixel, shows a technical fabric for filtering, with a 80 micron thick thread.
In the following figure, a series of images are analyzed by an Anomaly Detection Neural Network which depicts the output in blue for portions recognized as compliant and in red for non-compliant portions:
Specialvideo presents a 2D and 3D quality control for biscuits, crackers, breadsticks and leavened products. It can be integrated into robot lines, at a rate of over 1000 pieces/min.
The vision system for the quality control of biscuits verifies the integrity of the shape of the products and checks the fillings such as jam, cream and chocolate by quantity and position.
The application made for biscuits is suitable for other non-regular-shaped products such as crackers, chocolates, breadsticks and other baked goods.
For products as leavened products, in which height is a critical characteristic, we offer three-dimensional controls.
The system visually checks the cooking level. It detects the presence of any foreign bodies and pollutants that cause color anomalies.
To learn about the system, we invite you to read the case history and contact us for more information.
Specialvideo presents a quality control of Brilliant Uncirculated coins based on learning the model coin, thanks to which it determines the differences that cause discards, tolerating the variability due to the production process.
The concept of compliant currency is learned by the system by memorizing a series of coins free from gross defects or in any case having defects at different points of the coin. From that series, the system elaborates the model coin, therefore it takes into account the acceptable variability, due to the production process.
To learn about the system, we invite you to read the case history and contact us for more information.
The Company Profile of Specialvideo is available online in the Download section.
We create intelligent and efficient systems for the automation and quality control of your business
Specialvideo has been manufacturing vision systems for over 25 years and operates in various industrial sectors (automotive, pharmaceutical, and food just to name a few).
It offers technologically advanced solutions, custom-designed and supplied turnkey, for:
Specialvideo combines experience in 2D and 3D computer vision with Deep Learning research.
The first vision systems with neural networks are produced in 2019 and, to follow, new systems that include both neural networks and traditional techniques. The hybrid systems thus obtained have capabilities based on the strengths of both types of software: reliability, precision, and generalization.
The project starts from a preliminary study in the laboratory carried out on the samples provided by the customer, with attention to the specific needs of performance, integration into the production line and possible incorporation into Industry 4.0 projects.
During the construction phase, the choice of components and the quality controls of the software guarantee stability and reliability over time.
The Specialvideo team is made up of highly qualified professionals, employed in the development of new applications.
Over half of the Specialvideo systems are installed abroad and the company is structured to follow customers around the world, with particular attention to remote assistance to reduce costs and intervention times.
In the company profile, Specialvideo tells its story to date and presents the main applications areas.
