Artificial Intelligence lipstick (ENG)

Ever since its foundation, SEA Vision has focused its efforts in the field of industrial vision, aiming to improve continually and to overcome the limitations that typically emerge in packaging and automation processes. The portfolio of algorithms that underlie the SEA Vision software continues to evolve toward new horizons in AI.

At the Fair Interpack, SEA Vision shows to visitors the first glimpse of a new Artificial Intelligence technology applied to the visual inspection of lipsticks: a-eye lipstick.

Lipsticks - some of the most versatile, eclectic products, with complex quality control - pose very specific problems that require innovative solutions to enable their automated inspection.

The new Artificial Intelligence technology applied to the visual inspection of lipsticks is aimed to improve the inspection of a lipsticks, considered one of the world’s bestselling cosmetics.

Lipsticks are products that are complicated to produce and verify in terms of product quality: they come in fact in countless colours, finishes, shapes, formulations and combinations, and many of them, especially in the luxury sector, feature logos and sophisticated decorations impressed on the body or tip of the product.

These distinctive styling features - together with the complexity of the industrial process required to perfectly amalgamate the pigments, oils, waxes and emollients in its formula.

Even today, in spite of all the efforts made during production to prevent and control a whole series of potential defects, some flaws still pass through quality control undetected.

This leads to costly reprocessing: in the worst-case scenario, these products make it onto the market, implying serious risks for businesses in terms of brand reputation.

The SEA Vision system a-eye lipstick (under development together with ARGO Vision) uses the semantic segmentation of the areas of the lipstick (e.g. body, tip, neck, mechanism, etc.) to identify every possible flaw pixel by pixel. This is achieved by classifying areas by categories, each of which is assigned a name or “label”.

The system learns how to discern an ever-increasing variety of more and more complex defects, item-by-item. Learning takes place both on the basis of proprietary datasets - a mix of real and synthetic images generated with the most advanced data augmentation and neural generation techniques - and by combining the different models and parameters observed over time.

These deep learning-based semantic segmentation techniques, now the de facto standard in the Artificial Intelligence field, greatly accelerate the development of capabilities for the analysis of objects.

The learning process that defines the quality control algorithms continually evolves, to release increasingly sophisticated new versions.

The main feature of this innovation is the system’s ability to learn from past examples, constantly increasing its analysis capability, which is more or less what we humans do when we learn from experience.

Alessandro Ferrari

CEO Argo Vision

Our quality control systems cover a wide range of possible controls. Our tools take advantage of 20 years of experience in the use of image processing technologies, now combined with AI neural techniques.

Francesco Ringressi

Area Manager

We have used neural networks for the semantic segmentation of the images, in order to guarantee the ability to extract all the features from the many different types of lipsticks, to discriminate good and bad items.

Matteo Barbieri

Business Development Manager

The first glimpse of a-eye lipstick technology receives its public presentation at the start of what experts define as “the year of Artificial Intelligence”, in which the spread of technologies based on deep learning and neural networks is expected to make a big leap forward in quality terms.

SEA Vision showed the solution from live at Cosmopack and Interpack this year, and many other events are on plan!

In the meantime, if you want to know more, fill out the form to get in touch with our team and talk about our latest innovation for the cosmetic sector.

AI-based

Lipstick inspection: a-eye lipstick.

ARTIFICIAL INTELLIGENCE MAKES LIPSTICK QUALITY CONTROL SMARTER

Improve the inspection quality of a world's bestselling cosmetic

Why

What

How

Where

Lipsticks, a complex product

Some examples of the most common defects

When AI makes the difference

How many defects can you see?

Deep Learning based semantic segmentation

Smart lipstick inspection

Alessandro Ferrari

Francesco Ringressi

Matteo Barbieri

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