System for Reading Braille Embossed on Beverage Can Lids for Authentication

The paper describes a system for reading embossed Braille patterns on used aluminum beverage container lids. The intent of the system is to check whether the used containers are entitled to a refund. The lids have strong specular reflections. The reflections are avoided by a novel method that illuminates the lid alternating from two angles, and acquires two separate images. This illumination method is more compact than existing methods. We use the extended maxima algorithm to detect the Braille dots, and a cluster-based pattern point matching algorithm to recognize a pre-defined Braille pattern. The algorithms are customized to increase speed using a priori information. The system was evaluated on a test set containing 225 images. The median time used for analyzing one beverage can was 1 second, and the recognition rate was 94 percent.