In this research, we investigate face recognition with the Principal Component Analysis (PCA) technique and with Linear Discriminant Analysis (LDA) with Euclidean distance as the classifier. Many authors have used the Olivetti Research Laboratory (ORL) database and FERET face databases for these methods. Face recognition software employs memory to identify a given face image, usually via a training set that simulates a face recognizer’s memory. Although some studies have contrasted different techniques, a thorough examination of the subject is still absent. We intend to address this gap by examining the most widely used approaches and procedures and compiling the results of their numerical appraisals.
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