Ekstraksi Fitur Wajah Menggunakan Metode Viola Jones dengan Tools Cascade Detector - Perani Rosyani; Retnawati Retnawati (STMIK Budi Darma, 2023)
The face is an important part of a person's characteristics that can be recognized by their differences from one another. In image processing, extracting features from faces is the most crucial thing, because features such as the eyes, nose, mouth and human face are very complex to be recognized by a computer. One of them is how the computer can recognize faces and see them like human eyes. Feature extraction is needed in image processing so that the computer can recognize and differentiate facial objects. This cascade is a method used to detect objects and the algorithm has a high degree of accuracy. This method is considered fast and robust for face detection. From the results of the implementation of facial feature extraction using Cascade Detector, it can be concluded that the feature extraction results for the detection of the face and nose produce an accuracy of 85.2% while for the detection of the right eye, left eye and mouth produce an accuracy of 81.9%, which means this level of accuracy smaller than face and nose detection. For the average accuracy value of each extraction of facial features, right eye, left eye, nose and mouth, that is equal to 83.22%. With an error of about 3% because there are detected animal faces. For Animal Nose 1% is detectable