MODERN VOTING SYSTEM USING CNN MODEL

Abstract

Voting has usually been done using a project ballot, an Electronic Voting Machine (EVM) based on Direct Response Electronic (DRE), or Identical Ballot Boxes. In order to remedy the shortcomings of the current voting procedure, this paper suggests a digital voting system built on a Deep Learning algorithm that makes use of iris recognition. People can be identified by the iris pattern in their eyes thanks to a computer called the Iris recognition-based Voting System. Iris recognition is an automated biometric identity system that recognizes complex patterns that are distinct, stable, and observable from a distance by analyzing video evidence of one or both of an individual's iris. Voters are only allowed to cast one ballot, and the proposed technology will not allow the same voter to cast more than one since it will recognize duplicate entries. Furthermore, since the Aadhar is integrated with the voter ID, this technique eliminates the need for the user to carry a voter ID that contains the necessary information. This improves digitalization by using digital verification of the biometric and iris pattern available in each user's Aadhar card. An easy iris scan at the polling place will enable the voter's iris to be gathered and utilized for identification. The four processes involved in iris recognition are acquisition of the image, iris segmentation, feature extraction, and pattern matching. Because iris recognition has a high identification rate, it is one of the most reliable biometric modalities. Thus, by embracing the modern change, this method improves digital voting while eradicating the main shortcomings of conventional voting systems.