FINGER COUNTING SYSTEM USING OPENCV

Abstract

Human-Computer Interaction (HCI) is shifting towards natural, contactless Interfaces where gestures play a vital role. Finger Counting, a fundamental hand gestures, has applications in education, assistive technology, and touchless device control. Traditional systems use sensor gloves or contour-based image processing, which are either expensive or unreliable under changing conditions. This paper proposes a real-time finger counting system using Python, Opencv and mediaPipe. The system detects hand marks from a webcam feed and applies a landmark-based algorithm to count extended fingers accurately. The implementations achieve ~96% accuracy across varied backgrounds and lighting conditions.