IMPLEMENTATION OF AUTOMATIC HUMAN AGE ESTIMATOR

In this, paper review a new automatic age estimation framework is proposed. A single image is required to estimate the age of the subject of interest as a input. By using three main modules we are composed a framework which are:- 1) module of the face detection; 2) module of enhancement; and 3) the classification module. In case of classification module we are used unsupervised classification technique. K means algorithm is used which classified the features obtained from the Gabor filters of 6 directions and 4 scales. In the enhancement module of the proposed framework, the key for age estimation are facial regions which are identified by using a more detailed analysis. Finally, by utilizing the FG-net database we can calculate the application of human age estimation. The face detection module comprises the learning for age estimation and main blocks of image representation a. For age image representation, a technique named Adaboost which is modification of viola Jones algorithm is used.