Abstract
Secured authentication system is one of the most challenging tasks focused now-a-days by many researchers and greatly achieved by means of face detection technique. Face image recognition is currently realized by Adaptive singular value decomposition in two-dimensional discrete Fourier domain (ASVDF). The recognition systems ability enhancement is attained for face images recognition by side light influence reduction on a color face image for inadequate light. The prevailing researches does not focuses the following points: No correct output during face recognition process, Face spoofing is not concentrated thereby face recognition may effect in imprecise result, Optimal feature extraction. Optimized Face Recognition System with Illumination and Rotation Consideration (OFRS-IRC) is one of the promising solutions for mitigating all those issues. Various methods are presented for ensuring accurate face recognition. Additive White Gaussian Noise removal technique is utilized for eliminating noise when the image is captured through sensor devices. Illuminate invariant features and locality preserving projection approach is exploited for segmented image recognition. As a final step, Fuzzy neural network is deployed for precise prediction on the basis of locality preserving projection approach results. MATLAB simulation tool is exploited for evaluating this research, where improved performance are attained by proposed method than prevailing methods. The proposed method shows 7.42% better detection rate than the existing work.
Highlights
Additive White Gaussian Noise removal technique is utilized for eliminating noise when the image is captured through sensor devices
The illumination invariant has considered as the high-pass filter output, which can get utilized for recognition step, e.g. by principal component analysis (PCA)/linear discriminant analysis (LDA)
FALSE ACCEPT RATE (FAR) refers to an impostor probability, who has recognized as a genuine individual
Summary
Le et al [12] developed an approach namely Face Relighting As Data Augmentation (FRADA) for estimating 3D morphable model coefficients besides spherical harmonic lighting coefficients Various parameters such as face normals, face mask, face shading, and face albedo are extracted using this technique. The illumination effect for photometricbased human face recognition is elucidated by this optimized fuzzy-based illumination invariant technique. Dhekane et al [20] utilized uniform local binary patterns (uLBP) as well as Legendre moments for illumination as well as expression invariant face recognition technique. Thamizharasi et al [22] exploited 2D Discrete Cosine Transform as well as Contrast Limited Adaptive Histogram Equalization (CLAHE) for designing an illumination invariant face recognition system. The contrast adjustment is attained by CLAHE and computational complexity is reduced by resized images
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