Pengenalan Wajah Bebas Ekspresi Menggunakan Metode Nearest Feature Line dengan Representasi Ciri dalam Ruang Eigen
Abstract
Facial recognition with different expressions is one part of the pattern recognition problem which is quite complex when compared to pattern recognition on a normal profile.
The expression-free face recognition method using the Nearest Feature Line (NFL) technique works by finding the closest projection distance between feature vectors, assuming that the closer the projection distance of a feature vector (face) to another feature vector (face), the more similar the properties will be physical feature vector (face) which are close together. The NFL distance calculation is performed on the eigen dimensional space with the aim that the calculated feature vector (face) dimension has a much smaller dimension in order to increase the level of recognition accuracy and speed up computational time.
The test results obtained indicate the NFL method provides a fairly good level of recognition accuracy in the average value of 76.7% with the advantage of low computational time needed when compared with other intelligent methods such as artificial neural network systems.
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