Presentation of the results of the Vision and Artificial Intelligence project for leather classification, coordinated by Leather Cluster Barcelona

On Tuesday, September 6 at 4:30 p.m., the cluster is organizing a day at the Adoberia Bella to present the results and conclusions of the Vision and Artificial Intelligence project for the classification of leather, a project coordinated by Leather Cluster Barcelona where they are participating three associated companies: Intarex, Picvisa and Curtidos Badia.
This project has received funding from ACCIÓ (Department of Business and Knowledge), as part of the grants to strengthen the competitiveness of the entities that are members of the Catalonia Clusters Program 2021-2023.

 

 

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The aim of this collaborative project is to study the technical feasibility of a vision and artificial intelligence system for the automatic classification of skins, a technological solution that will allow companies to be more competitive by reducing costs and improving productivity.

Key factor for product quality

The classification of hides at the different stages of the leather transformation process is a key factor for the quality of the manufactured product, customer satisfaction and the bottom line of tanneries. It is a process that today is done manually, based on the expertise of workers with skills to carry out the operation for hours, based on mental patterns learned based on accumulating experience to discern between different types and combinations of defects, which allow each skin to be classified into different categories.

This is a very relevant operation due to the economic impact on the business, since the cost of leather as a raw material is usually approximately 50 percent of the total manufacturing cost.

 

The aim of this collaborative project is to study the technical feasibility of a vision and artificial intelligence system for the automatic classification of skins, a technological solution that will allow companies to be more competitive by reducing costs and improving productivity

 

The key technology in the project consists of using vision techniques and artificial intelligence for image processing. In particular, machine learning (deep learning) techniques will be used to build computational models that allow identifying what type of defect is present in an image: parasites, scratches, stab wounds, etc.

It is expected that in the future the project can be expanded to affect the traceability of skins.

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