Intelligent Rotation-Invariant Coin Identification System

摘要

The development of intelligent systems that simulate our ability to recognize and identify objects has been gaining momentum with the advances in image processing techniques and the use of neural networks. Rotated object identification is challenging for conventional recognition techniques simply due to the changes in pixel coordination. This paper presents a rotation-invariant intelligent coin identification system (ICIS) that uses averaged patterns of coins as the input data for a neural network classifier. Rotational invariance is provided by the averaged fuzzy feature vectors that represent the coins which are continuously rotated by 15 degrees. Currently, coin identification by slot machines relies on assessing the physical parameters of a coin. An intelligent coin identification system that uses coin patterns for identification helps preventing confusion between different coins of similar physical dimensions. Slot machines in Europe accept the new Turkish 1 Lira coin as a 2 Euro coin due to physical similarities; however, the 2 Euro coin is roughly worth 4 times the new Turkish 1 Lira. ICIS was implemented to identify the 2 EURO and the 1 TL coins and the results were found to be encouraging. This system is intended to be used as a support tool to standard physical measurements in slot machines.