A robust rotation invariant coin recognition system

Abstract

Coins have been the integral part of our day to day life since the ancient civilizations. In comparison to paper currency coin are easy to carry, requires less maintenance and can be used for a longer period of time. Moreover, commemorative coins issued by the governments were a common practice to mark important events and personalities. The coins are used frequently in places like grocery stores, banks, trains, buses, etc. With increase in coins usage and introduction of new automated machines that can use coin as a token to provide services, the need for coins to be recognized, counted, sorted automatically arises. In this thesis A Robust Rotation Invariant Coin Recognition System is proposed that takes into consideration various features of the coins (radius, color, rotation and texture) for the recognition. The system can recognize Indian coins of denominations of Rs.1, 2, 5 and 10. The system takes as input a RGB coin image of single side i.e. tail. The image is then pre-processed to remove the unwanted part to find out the radius using Hough transform. Then the color comparison is performed by comparing the RGB channels. After that rotation of the input coin is checked to find out whether it is rotated by using multi-level image subtraction technique. If the coin is rotated then it is rotated back to our desired position. In the end texture comparison is done using the LBP operator. If coin passes all the tests, then it will be recognized among one of the database coins. The system provides high recognition rate on the Indian coins as specified in given experimental results.