On utilizing smartphone cameras to detect counterfeit liquid food products

Counterfeit liquid food products, including olive oil, honey and alcohol, are continuing to pose severe threats to the general public as counterfeiters adulterate the authentic content with cheaper and potentially harmful substitutes, and package them in authentic bottles. Existing solutions are often impractical for the general public as they require specialized and costly equipment as well as taking liquid samples. We overcome these limitations by proposing LiquidHash, a novel detection system that only requires the use of a commodity smartphone to detect adulterated liquid products without opening the bottles. LiquidHash leverages computer vision and machine learning techniques to extract characteristics of air bubbles formed by flipping a bottle. We implement LiquidHash and evaluate its feasibility with real-world experiments and achieve an overall detection accuracy of up to 95%.