In order to address issues with manual vote counting during election procedures, this study intends to examine the viability of using advanced image processing techniques for automated voter counting. The study aims to shed light on how automated systems that utilize cutting-edge technologies like OpenCV, CVZone, and the MOG2 algorithm could greatly increase the effectiveness and openness of electoral operations. The empirical findings demonstrate how automated voter counting can enhance voting processes and rebuild public confidence in election outcomes, particularly in places where trust is low. The study also emphasizes how rigorous metrics, such as the F1 score, should be used to systematically compare the accuracy of automated systems against manual counting methods. This methodology enables a detailed comprehension of the differences in performance between automated and human counting techniques by providing a nuanced assessment. The incorporation of said measures serves to reinforce an extensive assessment structure, guaranteeing the legitimacy and dependability of automated voting systems inside the electoral sphere.

翻译：为应对选举过程中人工计票存在的问题，本研究旨在探讨采用先进图像处理技术实现自动化选民计票的可行性。研究重点阐明如何利用OpenCV、CVZone及MOG2算法等前沿技术构建的自动化系统，从而显著提升选举运作的效能与透明度。实证结果表明，自动化选民计票能够优化投票流程并重建公众对选举结果的信任，这在信任度较低的地区尤为显著。研究同时强调，应通过F1分数等严谨指标，系统化比较自动化系统与人工计票方法的准确度。该方法通过提供细致入微的评估，使研究者能够深入理解自动化与人工计票技术之间的性能差异。此类指标的纳入有助于强化综合评估体系，从而确保自动化投票系统在选举领域中的合法性与可靠性。