A real-time prototype system for identifying soda cans uses histogram
indexing with only 16 colors, with excellent results. The nal
implementation identied cans almost perfectly, even on public display
with many people attempting to fool it. Results from preliminary
versions are presented, with a complete description of the
circumstances used in training and testing the system. The nal system
required only 1.8 kilobytes of storage space for the database, 37
kilobytes of space for the program, and 70 milliseconds to process
each image, proving its suitability for implementation on an
autonomous mobile robot.
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