AI-Enhanced Speckle Pattern Imaging for Assessing Milk Authenticity

Valentina Bello, Irene Bassi, Cristina Nuzzi, Simone Pasinetti, Sabina Merlo

Abstract

Milk is daily consumed worldwide by billions of people and it is also one of the foods most commonly subject to adulteration and counterfeiting. This paper presents a novel low-cost approach to assess milk authenticity by combining speckle pattern imaging and artificial intelligence. From the collected images, 11 statistical parameters were extracted and used to train and test a machine learning model, with the aim of distinguishing whole cow milk and 8 adulterated samples. The performances achieved by the AI-enhanced speckle pattern imaging approach (accuracy of 80%) represent a promising starting point for the development of this label-free, low-cost, easy-to-use technique to support efforts in fighting food fraud.

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IMEKO-TC2-2025-015.pdf

DOI

10.21014/tc2-2025.015

IMEKO TC

TC2 - Photonics

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