Food appearance is critical information for estimating edibility, freshness and softness of foods. We developed some image processing techniques to modify the food appearance naturally. The first method is Luminance Distribution Manipulation (LDM). We found that LDM can modify the moistness and softness of foods in appearance. The second method is Visual Texture Exchange (VTE). VTE enables us to change the visual texture of a food from the original surface to other actual one, e.g. from Tuna to Salmon, and from Black Coffee to Café Latte in real time. The third method is Gloss/Shade Filter Operation (GSFO) which can create any Oily/Dried and Burned/Raw foods from an original food image in appearance. By applying such image processing methods and Augmented Reality technology, we are investigating crossmodal effects of food appearance to the taste while keeping the ingredients intact, indicating that we can artificially control the taste by modifying food appearance with image processing. Finally, I will introduce a novel approach to reduce salt by modulating saltiness by changing food appearances with Augmented Reality. We quantified the salt reduction effect by converting the perceived responses to match the amount of salt.

In this paper, I will introduce at the beginning the real-time evaluation of KANSEI using EEG, which the author has been working on for many years. Using this system, we have become able to analyze real-time emotional responses. The examples are shown in this paper. In addition, by measuring brain function using NIRS, the efficacy of oil against stress can be measured in real time.

Development races of private label brands are heating up in the domestic food industry. It is because consumer needs are diversifying year by year and need to respond them to survive in the market. Thorough pursuit of consumer needs is crucial in product developments. A taste sensor can visualize the needs into numerical data. As a result, a concept of product development becomes clear and therefore its target values are clarified. In the global market, taste preferences depending on regions are not easy to understand and communicate with each other through their own languages. To understand the differences, a common taste measure is required.

Palatability of foods depends on many factors, such as flavor, texture, and appearance. Textures such as crispness, crunchiness, hardness, and fragility are essential in many foods and evaluated by sensory tests in general. Although food scientists and engineers have attempted objective evaluations of the characteristic textures of different foods, an optimal method for the texture evaluation is yet to be developed. Here, we focused on the theory that texture can be evaluated based on the sound created during mastication. We developed a device mechanically capable of crushing foods. By combining this food crushing device with a method to analyze the crushing sounds, we aimed to construct an objective system for texture evaluation. In this report, we introduce our system and some acoustic analysis results. It is showed that the sounds of food crunched are useful to indicate its crispness objectively.