Face Recognition Across Age Progression By Using PCA (International Journal of Food and Nutritional Sciences, 2022)
In computer or automated system running through embedded software individual identity of human being can be established through face recognition system. Effectiveness of face recognition system has many challenges. One such challenge is age invariance. A face recognition system with the age invariance makes it robust but implementation is the most demanding. Aging brings about many changes in the structure and shape in the face. In this paper, an age-invariant face recognition system is proposed, which has four stages: Face Detection, Image Preprocessing, Feature Extraction and Feature Classification. Face Detection stage detects faces in the image .Face frontal alignment, cropping and noise removal is done in image preprocessing stage. Principal Component Analysis (PCA) is used to extract features of face in the image .Result of this analysis is achievement of the relevant features usable for age-invariant face recognition. Lastly, for classification multi support vector machine is used. The results show that the proposed system can be used efficiently in automated individual identification process and overcome challenges posed by aging. [1]