Detecting rice labelling fraud with smartphone photos
An investigation conducted by the Complutense University of Madrid (UCM) and the Scintillon Institute of San Diego has revealed that a photograph taken with a mobile phone can detect irregularities in the labelling of rice. Scientists developed an algorithm based on deep learning — a field of artificial intelligence — that uses the images taken with the smartphone to determine whether that rice is really the one described.
“What we contribute compared to other detection methods is simplicity and we show the consumer that you do not need large sums of money to verify whether a certain type of rice is the one mentioned on the label,” said José Santiago Torrecilla, Professor and researcher from the Department of Chemical Engineering and Materials of the UCM.
Researchers used five types of rice that were ground to distinguish the type of rice not only when it is in grain form, but also when it is ground into flour. Algorithms based on convolutional neural networks were designed and optimised to process the information contained in the images for classification based on the type of rice, with final precision models between 93% and 99%. This technology can also be extrapolated to other types of cereals or food, with many potential applications in the food industry.
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