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:

  1. Fully operational vision system with linear camera for inspecting solid colours.
  2. Colour acquisition for printed fabrics and weave inspection to train neural networks.
  3. Extension of colour functionality and definition of specifications for print and weave defects.
  4. Updating of the first system and supply of following systems complete with Artificial Intelligence.

Therefore, the first fabric inspection system installed in the factory has two purposes:

  • inspecting solid colours

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.

  • acquiring images of prints and weaves for the purpose of training AI

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.

Colour registration defect in patterned fabric
Colour registration defect in patterned fabric

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.

Our passion for the most innovative technologies is expressed since the first years of our activity.

Already in the early nineties, Specialvideo realized, in addition to 2D systems:

  • 3D systems, with laser projectors designed ad hoc, to search for the weld bead of pipes;
  • systems with self-learning statistics, the techniques that were then at the center of artificial intelligence, for the quality control of blisters and food products;
  • proprietary algorithms for finding the valve hole notch in raw castings of light alloy wheels, still in high performance production;
  • calibrated (precision) measuring systems for the control of keys, also adopting telecentric optics.

Just one year after its foundation, in 1994, Specialvideo implemented the first  robot guidance with conveyor tracking, and expanded the range of technologies with the introduction of linear cameras and color cameras.

In the same years Specialvideo adopted LED lights, which were not yet a standard and therefore required a special card for adjustment and synchronization with the cameras, which were analogue at the time. In the late nineties, the first digital cameras arrived on the market, which Specialvideo adopted for a rapid evolution of its vision systems.

In 2023, Specialvideo has found the strategic partner for the development of the company: G.D S.p.A., a company of Coesia group, which participates with a minority stake.

A rapid succession of new technologies, integrated into our systems year after year, has led us to celebrate 30 years of activity with cutting-edge vision systems.

We thank our team of colleagues, customers, suppliers and partners who make all this possible.

The mass-produced “smart camera” vision systems can sometimes not have the solutions to specific automation needs that industries face to distinguish themselves in their sector. Then you can choose a vision system designed ad hoc by Specialvideo, made with equipment commensurate with its production lines and equipped with software developed in accordance with its production processes.

The project starts from a preliminary study in the laboratory carried out on the samples supplied by the customer, with attention to the specific performance needs, integration into the production line, and possible incorporation into Industry 4.0 projects.

In the creation of an ad hoc designed vision system, the cameras, the optics, and the light sources are specially selected to integrate into the customer’s production line, respecting the spaces of the pre-existing mechanical parts and acquiring images with specially designed lighting. The artificial vision software is developed to achieve the required performance and optimized to process within the normal production process times.

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 selection of cameras combined with appropriate high quality optics
  • the study of lighting and background, to enhance the details of the product and its defects
  • the design of the motion scan to inspect 100% of the product surface
  • the design and development of the application code, with classic Computer Vision and Deep Learning, also combined in hybrid solutions based on the strengths of both types of software: reliability, precision and generalization.

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.

Scanner per ispezione del prodotto al 100%: tessuto tecnico per filtraggio con scala risoluzione

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:

Scanner per ispezione del prodotto al 100%: tessuto tecnico per filtraggio ispezionato da rete neurale

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.

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