z-logo
open-access-imgOpen Access
Age Estimation Based on CLM, Tree Mixture With Adaptive Neuron Fuzzy, Fuzzy Sum
Author(s) -
Mohammad Saber Iraji,
Mohammad BagherIraji,
Alireza Iraji,
Razieh Iraji
Publication year - 2014
Publication title -
international journal of image graphics and signal processing
Language(s) - English
Resource type - Journals
eISSN - 2074-9082
pISSN - 2074-9074
DOI - 10.5815/ijigsp.2014.03.07
Subject(s) - fuzzy logic , tree (set theory) , estimation , computer science , artificial intelligence , adaptive neuro fuzzy inference system , mathematics , statistics , fuzzy control system , economics , combinatorics , management
As you know, age diagnosis based on the image is one of the most attractive topics in computer .In this paper, we present a intelligent model to estimate the age of face image. We use shape and texture feature extraction from FG-NET landmark image data set using AAM(Active Appearance Model), CLM (Constrained Local Model), tree Mixture algorithms. Finally, the obtained features were given as the training data to the ANFIS (adaptive neuro fuzzy influence system), FSVM (Fuzzy Support Vector Machine). Our experimental results show that In our proposed system, fuzzy svm has less errors and system worked more accurate and appropriative than prior methods. Our system is able to identify age of face image from different directions as is

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom