Algorithm 1: Determine human eye color intensity and age estimation

Input: a sequence of images or an image. Output: the predicted age or ages. 1.Read a sequence of images or an image. 2.In the image preprocessing stage, Perform: 3.  Apply various operations, such as filtrations, DWT, and PCA, to remove noise, resize and convert inputs to gray ones. 4.  Perform several filtration processes on inputs to enhance pixels. 5.End of the image preprocessing stage. 6.Perform the Viola-Jones method to detect a face, then eyes. 7.In the deep learning stage, Do: 8.  Analyze detected colors of eyes and perform deep learning using CNN. 9.  For i = 1: the size of the processing images 10.    For j = 1: the size of the processing images 11.      Remove unwanted pixels outside the borders of the detected eyes. 12.      Compute pixels sum to the standard deviation. 13.      Determine a mean of standard deviation for color values. 14.    End 15.  End 16.End of the deep learning stage. 17.Predict ages and display computed outputs. 18.Calculate the required performance metrics: accuracy, MSE, MAE, precision, recall, and F-score. 19.End of algorithm