Electoral system is a kind of voting system which is also known as majority voting system where the winner of an election is the candidate that received more than half of the votes cast. Since, this project is focused on automation of the Electoral system. Here, the system is developed such that it can detect the faces and raised hand of people and generate the total counts of faces and hands detected. This project is HCI based system where the raised hand of human is detected in order to track the vote of the people. The main objective of this project is to use computer vision and an important mode of interaction i.e. hand gesture to cast the vote. In order to design the proposed system, Haar Cascades Classifier (HCC) is used to detect the faces and hands. Haar-features are good at detecting edges, also has a higher execution speed and less computations are involved so, Haar-based classifiers are applicable in the proposed system. The system was found to be 86% accurate for face detection and 71% accurate for raised hands detection. The results imply, use of normal cameras do not produce high accurate results so, higher resolution cameras or IR cameras could improve the accuracy of the system significantly