The SP-MILK dataset: A comprehensive dataset of speckle pattern images of pure and adulterated milk samples

Speckle pattern (SP) imaging is an optoelectronic technique that can be used to analyse suspensions and opaque liquid foods, such as milk. When coherent light interacts with a diffusive sample, it is back-scattered and it generates an interference pattern, called speckle pattern, that contains information about the physical and compositional properties of the material. Images of the produced SP can be collected with a camera and analysed. In recent years, studies in the scientific literature have started demonstrating how the analysis of SP images can help in distinguishing milk samples with different nutritional characteristics and detect possible adulteration. However, the availability of public datasets of SP images is still very limited, and the datasets currently available mainly include measurements of unadulterated milk samples only. To address this gap, we present the SP-MILK dataset, which contains images of speckle pattern acquired from both pure and milk samples intentionally adulterated and prepared in the laboratory. Images were obtained from cow milk and goat milk in the unadulterated case. For the adulterated case, we considered dilutions of whole cow milk with water and with water-glucose solutions in different proportions. The data were collected using an experimental setup in which a coherent light source illuminates the samples and a CMOS camera records the resulting SPs. The SP-MILK dataset is intended to support the development and evaluation of computational methods for milk characterization and adulteration detection, and to provide a reference dataset for future studies based on SP data.