Analysis of methods for the recognition of Indian coins: A challenging application of machine vision to automated inspection

Abstract

The subject of this paper is a particularly challenging machine vision (MV) based sorting application where the ‘part’ is an Indian coin. The application is challenging in part because of the lack of distinctive features to differentiate between denominations as well as the variability in the features for a given denomination. Although there are coin recognition algorithms documented in the literature, the applications are typically tested off-line with static images of the coins. In this paper, a MV-based system for on-line recognition and counting of Indian coins moving on a conveyor is evaluated. The accuracy and performance of three different techniques are compared: particle classification, pattern matching and geometric matching. The conclusion is that none of these three techniques produced acceptable results, where the goal was to achieve 95% accuracy at 1000 coins/min.