Fine-Grain Prediction of Strawberry Freshness using Subsurface Scattering

Predicting fruit freshness before any visible decay is invaluable in the food distribution chain, spanning producers, retailers, and consumers. In this work, we leverage subsurface scattering signatures associated with strawberry tissue to perform long-term edibility predictions. Specifically, we implement various active illumination techniques with a projector-camera system to measure a strawberry’s sub-surface scattering and predict the time when it is likely to be inedible. We propose a learning-based approach with captures under structured illumination to perform this prediction. We study the efficacy of our method by capturing a dataset of strawberries decaying naturally over time.