Age Estimation from Face Image using Wrinkle Features

被引：15

作者：

Jana, Ranjan ^{[1
]}

Datta, Debaleena ^{[1
]}

Saha, Rituparna ^{[1
]}

机构：

[1] RCC Inst Informat Technol, Kolkata 700015, India

来源：

PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGIES, ICICT 2014 | 2015年 / 46卷

关键词：

Age estimation; face feature; feature extraction; fuzzy c-means; wrinkle feature;

D O I：

10.1016/j.procs.2015.02.126

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Age progression is generally indicated by skin texture, face structure, skin color. The face features changes with age progression of a human. This paper provides a methodology to estimate the real age of a human by analyzing wrinkle area of face images. Wrinkle geography areas are detected and wrinkle features are extracted from face image. Depend on wrinkle features, each face image is clustered using fuzzy c-means clustering algorithm. Then, estimated age is calculated using their clustering membership value and average age of each cluster. The obtained results are significant and remarkable. (C) 2015 The Authors. Published by Elsevier B.V.

引用

页码：1754 / 1761

页数：8

共 18 条

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