Age Classification for work sustainability using SVM using Co-occurrence features on Fibonacci Weighted Neighborhood Pattern Matrix

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Computer vision systems are increasingly focusing on age recognition from facial images. To solve this problem, In this paper, proposed a method that computes the Fibonacci Weighted Neighborhood Pattern on an image to obtain local neighborhood information, then evaluates Co-occurrence features for work sustainability age classification with SVM classifier. These characteristics show how people’s ages differ. The proposed method has been tested on the FG-Net facial images dataset as well as other scanned images. Experiments showed that the proposed approach outperformed other currently existing methods.