Age Estimation Based on CLM, Tree Mixture With Adaptive Neuron Fuzzy, Fuzzy Svm

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Author(s)

Mohammad Saber Iraji 1,* Mohammad Bagher Iraji 2 Alireza Iraji 2 Razieh Iraji 2

1. Department of Computer Engineering and Information Technology, Payame Noor University, I.R. of Iran

2. Department of Engineering, Damavand Branch, Islamic Azad University ,Science and Research Branch, Damavand ,Iran

* Corresponding author.

DOI: https://doi.org/10.5815/ijigsp.2014.03.07

Received: 16 Oct. 2013 / Revised: 29 Nov. 2013 / Accepted: 7 Jan. 2014 / Published: 8 Feb. 2014

Index Terms

Face Age, AAM, CLM, Tree Mixture, Fuzzy Svm, Anfis

Abstract

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.

Cite This Paper

Mohammad Saber Iraji, Mohammad Bagher Iraji, Alireza Iraji, Razieh Iraji,"Age Estimation Based on CLM, Tree Mixture With Adaptive Neuron Fuzzy, Fuzzy Svm ", IJIGSP, vol.6, no.3, pp.51-57, 2014. DOI: 10.5815/ijigsp.2014.03.07

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