Melon Authentication by Agri-biometrics - Identifying Individual Fruits using a Single Image of Rind Pattern

We propose a new method of biometric authentication, called agri-biometrics that identifies an individual fruit using a single image of its rind patterns. Our proposed method normalizes the rotations in depth of the fruit and extracts a set of image features, which are compatible to the 'minutiae', from the normalized image; thus, it enables us to apply a state-of-the-art technique of fingerprint matching to identify the rind patterns of fruit. We conducted large-scale experiments to identify/verify 1,776 individual melons in practical situations where the images were taken under different pose and illumination conditions on different days. Our method in the experiments achieved excellent recognition of EER=0.06%. The agri-biometric authentication we propose accomplishes 'verifiable' agri-food traceability and brand protection; once the producers register pictures of their products into the database, anyone can verify the products on hand with the camera of a mobile phone.