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What we taste is affected by what we see, and that includes the colour, opacity, and shape of the food we consume. We report two experiments designed to investigate how the standard deviation (SD) of the luminance distribution of food images influences the perceived visual texture and the taste/flavour experience by using the latest Augmented Reality (AR) technology. We developed a novel AR system capable of modifying the luminance distribution of foods in real-time using dynamic image processing for simulating actual eating situations. Importantly, this form of dynamic image manipulation does not change the colour on the food (which has been studied extensively previously). Instead, the approach outlined here was used to change the SD of the luminance distribution of the food while keeping the chromaticity, the average luminance, and the skewness constant. We investigated the effects of changing the luminance SD distribution of Baumkuchen (a German baked cake) and tomato ketchup on visual perception, flavour expectations, and the ensuing taste experience. Participants looked at a piece of Baumkuchen (Experiment 1) or a spoonful of tomato ketchup (Experiment 2) having different luminance distributions and evaluated the taste on sampling the food. Manipulating the SD of the luminance distribution affected not only the expected taste/flavour of the food (e.g. expected moistness, wateriness and deliciousness), but also the actual taste properties on sampling the food itself. The novel food modification method and system outlined here can therefore potentially be used to control the taste/flavour of different foods crossmodally by means of modifying their appearance properties (specifically the SD of the luminance distribution while keeping other aspects of image statistics constant), and can do so in real time, without the need for food markers.

Effects of varying the standard deviation of the luminance on the appearance of food, flavour expectations, and taste/flavour perception