Face recognition template in photo indexing: A proposal of hybrid Principal Component Analysis and triangular approach (PCAaTA)

Abstract

Many features of human faces play important roles in designing a method that can perform face recognition. There are many current studies in the area of face recognition, but most of them have limitations. The Principal Component Analysis (PCA) is one of the best facial recognition algorithms. However, there are some noises that could affect the accuracy of this algorithm. The PCA works well with the supports of preprocessing steps such as illumination reduction, background removal and color conversion. Some current solutions have showed result in using combination of PCA and preprocessing steps. This paper proposes a hybrid solution in face recognition using PCA as the main algorithm with the support of triangular approach in face normalization in order to enhance the accuracy. To evaluate, the proposed approach is tested and the results are compared with the current solutions.

Schoenberg Logarithmic Image Similarity in Prewitt-Gabor-Zernike Domain

“…It is a multidisciplinary filed with many unresolved problems that involve several other fields especially mathematics, numerical analysis, statistics, computer science and electronic engineering (Parmar and Mehta, 2013;Vu et al, 2016;Nagi et al, 2008;Alwakeel and Shaaban, 2010). One of the main streams in face recognition is to recognize a given face image in the sense of similarity with some image in a large face-database.…”