Layer counting

Subpixel embarked on a challenging project to automate the counting of stacked leather sheets, a critical component in automotive part production. Leveraging deep learning techniques, our team developed a sophisticated solution designed to address the unique complexities of this task.

Project Challenges:

  • Variable Layer Thickness: The leather sheets varied significantly in thickness, presenting a considerable challenge for accurate counting.
  • Detection of Layer Borders: Identifying the borders between layers proved to be exceptionally difficult due to the subtle distinctions in texture and color.

Innovative Approach:

– Deep Learning Techniques: We applied advanced deep learning algorithms tailored to recognize and differentiate the nuanced characteristics of each leather sheet, despite the variations in thickness and the elusive nature of the layer borders.


The solution enhanced the efficiency and accuracy of the counting process for stacked leather sheets, crucial for maintaining inventory accuracy and production scheduling in automotive manufacturing. This project not only demonstrated Subpixel’s capability to solve highly specific and complex problems through innovative technology but also improved a key manufacturing process for our client.

[Note: Imagery is representative due to a non-disclosure agreement.]

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