Gene expression programming based age estimation using facial features
Ashutosh Ashutosh, Baddrud Zaman Laskar, Sunil Kumar, Swanirbhar Majumder · 2013
The core target of this paper is to estimate human age automatically through facial image analysis. In this research study we put forward a system constructed on the basis of Gene Expression Programming (GEP) to estimate human ages using face features. Gene expression programming (GEP) is a handy tool to find out functions. Due to prompt developments in machine vision and computer graphics, age estimation through faces have turn out to be most dominant issues now a days due to their widespread applications in real world, such as safety control, investigation monitoring, biometrics, scientific art, automated client relationship management and cosmetology. As it is difficult to estimate the actual age, our system is going to estimate the ages within certain ranges. Total age range is classified into four classifications which differentiate the individual's oldness in relation with age. Our proposed approach has been initialized with GEP and then developed and tested using MATLAB. A public data set, FG-NET was used to develop the system. The quality of the proposed system for image-based age estimation is shown by broad experiments on the available database of FG-NET. To assess the performance of our system, we have done a relative study based on various parameters of GEP and found significant results.