Recognition of Handwritten Currency Symbols using Fuzzy Inference System
Arshia Gupta · International Journal for Research in Applied Science and Engineering Technology · 2021
In recent years, soft computing techniques have played an important role in the field of Handwritten Recognition. These techniques have been applied by different researchers to recognize handwritten scripts, alphabets, characters and so on. But no system has been proposed for the recognition of handwritten currency symbols. In this study, an automated intelligent system has been presented to recognize the handwritten currency symbols efficiently using Fuzzy Inference System (FIS). The experimental study has been conducted on the real dataset of the handwritten currency symbols of five topmost Asian richest countries. FIS has been implemented with subtractive clustering (SC) and fuzzy c-means (FCM) methods. The experimental result predicted that FIS with Subtractive Clustering achieved accuracy of 96.4% whereas FCM based FIS predicted 84% accuracy; hence SC-FIS outperformed FCM-FIS.