Alumni Face Recognition Using Fisherface Method

Abstract

Face is part of the human body that became one of the uniqueness and characteristics of each individual. From time to time changes in the face will of course happen by many factors, especially age, in this case the face of alumni. Alumni is a group of people who have attended or graduated from a school or college. One of the technologies used to identify faces is facial recognition. Fisherface is one of the methods used to recognize a person's face. This study has produced a system that can help search alumni information quickly only by using face variable. Testing has been done by taking a face image using a face detector that has been inserted in the face recognition application on Android. Taken image data will be matched with the training data that has been stored in the database using the Euclidean Distance approach. The Euclidean distance between the training data and the test image data will then be calculated and searched for the lowest distance between those two. The lowest Euclidean distance means that the test image data tested has a high degree of compatibility with the training data. From the tests results can be concluded that the Fisherface method can recognize well test image data using 150 training data and 75 test image data with 100% accuracy percentage on neutral face, 80% on smiling face, 60% on face with glasses attribute, 86.66% with make-up, and 100% with sideways face.