An eye detection system using Python is a computer vision application that uses image processing techniques to detect eyes in an image or video stream. The system uses a pre-trained classifier to identify the eyes based on their features and distinguish them from other parts of the face.
The most common approach for eye detection is using the Haar Cascade classifier, which is a machine learning-based algorithm that uses a set of positive and negative images to train a model that can detect the target object, in this case, eyes. The classifier works by analyzing the differences between the light and dark areas of the image and identifying patterns that correspond to the target object.
Once the eyes are detected, the system can perform various operations, such as tracking the movement of the eyes or measuring the distance between the eyes. Eye detection systems have a wide range of applications, including security systems, human-computer interaction, and medical diagnosis.
Python provides many computer vision libraries, such as OpenCV, that offer built-in functions for image processing and object detection. By using these libraries, developers can quickly build a robust and accurate eye detection system that can work in real-time with high efficiency