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

¹ CSE Department, Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad, Telangana, India
² CSE Department, Vidya Jyothi Institute of Technology, Hyderabad, Telangana, India
³ CSE Department, Matrusri Engineering College, Hyderabad, Telangana, India
⁴ CSE Department, CVR College of Engineering, Hyderabad, Telangana, India
⁵ Uttaranchal Institute of Management, Uttaranchal University, Dehradun, India
⁶ Department of Information Technology, TKR College of Engineering and Technology, Hyderabad, Telangana, India

^* Corresponding author: pchandureddy@yahoo.com

Abstract

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.