Smart Voting System Using Deep Learning and Computer Vision

Abstract

Abstract: Since, India being the largest democracy in the world. Still uses voting machines to hold elections, which comes with high costs and manual labour. But voting plays a crucial role in the election of high-ranking government officials and reflects our view of how a governing body should be formed. Investigations are conducted from time to time to troubleshoot the central voting system, increasing anonymity, credibility and security while preventing all types of fraud. In this paper, there is an implementation of a method that uses deep learning techniques which develops a smart voting system. Due to its advanced features, most researchers follow and use the Boosted Cascade framework. The enhanced Cascade Framework features help you calculate and build a classifier that works more accurately. However, this accuracy rate requires a large number of Cascade Stages to help reduce similar performance with the detection and recognition accuracy. This provides protection in the sense that the most secure voter password is verified before a vote is received on the main database of the Indian Electoral Commission and voters can verify that his or her vote has reached to correct participant of election. The votes counting is done automatically, thus saving a lot of time and the results can be announced in a very short time by the Indian Electoral Commission. The user verification process is enhanced by adding a face recognition to the app that will determine whether the voter is a certified user or not. Keywords: Online voting system, smart voting, face recognition, face detection, security, user authentication, deep learning, haar cascade classifier, computer vision.