SP-MILK: a dataset of speckle pattern images of pure and adulterated animal milk
Authors/Creators
Description
This dataset contains a total of 12 000 speckle pattern images of milk samples captured using an optoelectronic setup involving a CMOS camera and a red laser source. The data is divided into two sub-datasets: the "unadulterated" samples refer to milk samples without adulteration, while the "adulterated" samples refer to milk samples obtained by diluting pure cow milk with water and a mix of water and glucose. The tested samples are the following:
Unadulterated dataset:
- R: powdered dextrose (reference sample)
- S1: whole cow milk UHT
- S2: partially skimmed cow milk UHT
- S3: skimmed cow milk UHT
- S4: whole goat milk UHT
- S5: partially skimmed goat milk UHT
Adulterated dataset:
- RAD: powdered dextrose (reference sample)
- SAD1: whole cow milk UHT
- SAD2: whole cow milk UHT adulterated with a 15% water dilution (17 ml milk, 3 ml water)
- SAD3: whole cow milk UHT adulterated with a 30% water dilution (14 ml milk, 6 ml water)
- SAD4: whole cow milk UHT adulterated with a 15% water+glucose dilution (17 ml milk, 3 ml water+glucose)
- SAD5: whole cow milk UHT adulterated with a 30% water+glucose dilution (14 ml milk, 6 ml water+glucose)
The file "filenames_and_labels" links the specific SP filename to the class label (the sample) and also contains the folder structure, helping researchers dynamically build the full path to the images for data analysis.
Please remember that measurement noise due to the instrumentation and sample internal variabilities among preparations must be corrected using the data of the reference samples.
Additional details about the optoelectronic setup, the samples' preparation, the data acquisition procedure, and the dataset validation can be found in the related data article and scientific articles in the "References" section. Please cite them if you use this dataset for your research.
Files
ADULTERATED_CAMP1.zip
Files
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Additional details
Funding
- Ministero dell'università e della ricerca
- MUSKETEER: Milk adUlteration detection using SpecKlE paTtern and machinE lEaRning P2022FX228
References
- I. Bassi, C. Nuzzi, S. Pasinetti, V. Bello, "Advancing food safety through AI-driven speckle pattern imaging for milk adulteration detection," Proc. SPIE 13887, Photonic Technologies in Plant and Agricultural Science III, 138870A (5 March 2026); https://doi.org/10.1117/12.3078439
- I. Bassi, V. Bello, C. Nuzzi, S. Pasinetti, and S. Merlo, "The MUSKETEER project: milk adulteration detection using speckle pattern and machine learning", Proc. SPIE 13527, Optical Sensors 2025, 1352704 (23 May 2025); https://doi.org/10.1117/12.3055267
- I. Bassi, C. Nuzzi, S. Pasinetti, V. Bello, "The SP-MILK dataset: A comprehensive dataset of speckle pattern images of pure and adulterated milk samples", Data in Brief, vol. 67, 2026, 113009; https://doi.org/10.1016/j.dib.2026.113009