Teknik Pengenalan Wajah Menggunakan Model Ekstraksi Fitur Citra Digital

Abstract

The use of information technology has been widely encountered in our daily life. Not only to process data, to record tools but also to identify and recognize human characteristics. This is called biometric technology. This technology identifies the unique and permanent parts of the human body such as fingerprints, eyes, and the shape of the human face. To identify and recognize human faces, use facial image processing and analysis, such as determining the component regions of the human face and their characteristics. Splitting the face image into facial components, then extracting it into the features of the eyes, nose, mouth, and chin. The distance between each component is measured, then combined with other features to form facial semantics. The face can be categorized into the T Zone which consists of the forehead, eyes, nose and mouth. Eyes, nose, and mouth are the most unique facial components for facial recognition because they have unique facial recognition features. For the distance of the eye and mouth triangle feature, J1 – J3 shows that there are 140 unique data with the percentage value is 93.33%. The feature distance J4 – J6 also shows that there are 126 unique face images with a percentage value of 85%. Keyword: face image, eiginfaces, image extraction, face recognition.