Cream Detection with AI

Cream Detection with AI

In high-speed biscuit manufacturing lines, cream consistency, placement, and quantity are critical to product quality and customer satisfaction. BT Print’s AI-powered Cream Detection System uses advanced image processing and segmentation techniques to inspect every biscuit for cream presence, volume, and alignment—even when dealing with similar color overlays and textured surfaces like cream crackers.

This system is especially useful for sandwich biscuits, cream crackers, and other confectionery items where layer accuracy and visual appeal are essential.



How the System Works:

  • High-resolution vision sensors capture images of cream biscuits on the conveyor.
  • AI-based segmentation isolates the cream layer on each biscuit, distinguishing it from the biscuit base—even with close color similarity.
  • It calculates the percentage of cream coverage, thickness, and position symmetry.
  • Biscuits with missing cream, underfilled centers, or off-position layering are automatically flagged for rejection.


Key Features & Benefits:

  • Real-time detection of cream presence and alignment on each biscuit
  • AI segmentation of cream, even with similar color overlays or textured surfaces
  • Measures cream quantity and percentage coverage accurately
  • Ideal for products with dual-layer or sandwiched cream applications
  • Reduces manual QC effort while increasing output consistency
  • Supports reject mechanisms to remove under-processed or off-spec biscuits
  • Can be trained to different biscuit shapes, sizes, and cream colors
  • Logs detailed inspection data for quality trend analysis and audits
  • Increases consumer satisfaction with uniform product quality


This AI inspection solution is tailored for biscuit factories, snack food producers, and confectionery lines seeking to enhance their product quality with precision and automation.

BT Print’s Cream Detection System brings a new layer of intelligence to food manufacturing, helping you maintain consistency while reducing human error.



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