Face recognition is one of the most important image processing research topics which is widely used in personal identification, verification and security applications. In this paper, a face recognition system, based on the principal component analysis (PCA) and the feedforward neural network is developed. The system consists of two phases which are the PCA preprocessing phase, and the neural ne...

• We propose a general framework that is suitable for the de-identification of people in face images. are first to introduce rigorously formulated DP theory into face-anonymous task. Our method does not require special training or targeted adjustments many unauthorized identity verification systems datasets never seen before. show images anonymized by our still usable identity-agnostic computer...

In low light conditions, visible light face identification is infeasible due to the lack of illumination. For nighttime surveillance, thermal imaging is commonly used because of the intrinsic emissivity of thermal radiation from the human body. However, matching thermal images of faces acquired at nighttime to the predominantly visible light face imagery in existing government databases and wat...

Three experiments examined whether image manipulations known to disrupt face perception also disrupt visual speech perception. Research has shown that an upright face with an inverted mouth looks strikingly grotesque whereas an inverted face and an inverted face containing an upright mouth look relatively normal. The current study examined whether a similar sensitivity to upright facial context...

Problem statement: In facial biometrics, face features are used as the required human traits for automatic recognition. Feature extracted from face images are significant for face biometrics system performance. Approach: In this thesis, a framework of facial biometric was designed based on two subspace methods i.e., Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). Firs...

Face recognition is one of the most active areas of research in computer vision. Gabor features have been used widely in face identification because of their good results and robustness. However, the results of face identification strongly depend on how different are the test and gallery images, as is the case in varying face pose. In this paper, a new Gabor-based method is proposed which modif...