CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

Facial Wrinkles Detection Techniques and its Application

by Ashwini Mawale, Archana Chaugule
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 134 - Number 7
Year of Publication: 2016
Authors: Ashwini Mawale, Archana Chaugule
10.5120/ijca2016907826

Ashwini Mawale, Archana Chaugule . Facial Wrinkles Detection Techniques and its Application. International Journal of Computer Applications. 134, 7 ( January 2016), 5-8. DOI=10.5120/ijca2016907826

@article{ 10.5120/ijca2016907826,
author = { Ashwini Mawale, Archana Chaugule },
title = { Facial Wrinkles Detection Techniques and its Application },
journal = { International Journal of Computer Applications },
issue_date = { January 2016 },
volume = { 134 },
number = { 7 },
month = { January },
year = { 2016 },
issn = { 0975-8887 },
pages = { 5-8 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume134/number7/23924-2016907826/ },
doi = { 10.5120/ijca2016907826 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:33:29.600830+05:30
%A Ashwini Mawale
%A Archana Chaugule
%T Facial Wrinkles Detection Techniques and its Application
%J International Journal of Computer Applications
%@ 0975-8887
%V 134
%N 7
%P 5-8
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Face recognition is process of identifying or verifying individual person by their face. One of the most important sources of the information is human face which can be intended for personal verification and identification of individual person. Wrinkles play an essential role in age estimation. They have been commonly used in applications, such as face age estimation, facial retouching and facial expression recognition. Facial wrinkles present 3D form of skin and appear as skillful discontinuities or cracks in surrounding skin texture. There are different techniques present for facial wrinkles detection. This paper presents the study and review of various techniques used in wrinkle detection. This paper is motivated by need of fast and robust algorithm for detection and classification of human age and facial retouching.

References
  1. Fu, Yun, Guodong Guo, and Thomas S. Huang. "Age synthesis and estimation via faces: A survey." Pattern Analysis and Machine Intelligence, IEEE Transactions on 32.11 (2010): 1955-1976.
  2. Choi, Sung Eun, et al. "Age estimation using a hierarchical classifier based on global and local facial features." Pattern Recognition 44.6 (2011): 1262-1281.
  3. Dehshibi, Mohammad Mahdi, and Azam Bastanfard. "A new algorithm for age recognition from facial images." Signal Processing 90.8 (2010): 2431-2444.
  4. N.Ramanathan, R.Chellappa, “Modeling shape and textural variations in aging faces, in:FG,2008,pp.1–8..
  5. Jana, Ranjan, Debaleena Datta, and Rituparna Saha. "Age Estimation from Face Image Using Wrinkle Features." Procedia Computer Science 46 (2015): 1754-1761.
  6. Luu, Khoa, et al. "Combined local and holistic facial features for age-determination." Control Automation Robotics & Vision (ICARCV), 2010 11th International Conference on. IEEE, 2010.
  7. Ramanathan, Narayanan, Rama Chellappa, and Soma Biswas. "Computational methods for modeling facial aging: A survey." Journal of Visual Languages & Computing 20.3 (2009): 131-144.
  8. Y. H. Kwon and N. da Vitoria Lobo, ‘‘Age classification from facial images,’’ Comput. Vis. Image Understand., vol. 74, no. 1, pp. 1–21, 1999.
  9. Yin, Lijun, and Anup Basu. "Generating realistic facial expressions with wrinkles for model-based coding." Computer vision and image understanding 84.2 (2001): 201-240.
  10. Huang, Yizhen, Ying Li, and Na Fan. "Robust symbolic dual-view facial expression recognition with skin wrinkles: local versus global approach."Multimedia, IEEE Transactions on 12.6 (2010): 536-543.
  11. Park, Gyu-tae, and Zeungnam Bien. "Fuzzy observer approach to automatic recognition of happiness using facial wrinkle features." Fuzzy Systems Conference Proceedings, 1999. FUZZ-IEEE'99. 1999 IEEE International. Vol. 3. IEEE, 1999.
  12. Ohchi, Shuji, Shinichiro Sumi, and Kaoru Arakawa. "A nonlinear filter system for beautifying facial images with contrast enhancement." Communications and Information Technologies (ISCIT), 2010 International Symposium on. IEEE, 2010.
  13. Arakawa, Kaoru. "Nonlinear digital filters for beautifying facial images in multimedia systems." Circuits and Systems, 2004. ISCAS'04. Proceedings of the 2004 International Symposium on. Vol. 5. IEEE, 2004.
  14. Batool, Nazre, and Rama Chellappa. "Detection and inpainting of facial wrinkles using texture orientation fields and markov random field modeling." Image Processing, IEEE Transactions on 23.9 (2014): 3773-3788.
  15. Batool, Nazre, Sima Taheri, and Rama Chellappa. "Assessment of facial wrinkles as a soft biometrics." Automatic Face and Gesture Recognition (FG), 2013 10th IEEE International Conference and Workshops on. IEEE, 2013.
  16. Batool, Nazre, and Rama Chellappa. "Modeling and detection of wrinkles in aging human faces using marked point processes." Computer Vision–ECCV 2012. Workshops and Demonstrations. Springer Berlin Heidelberg, 2012.
  17. Batool, Nazre, and Rama Chellappa. "A Markov point process model for wrinkles in human faces." Image Processing (ICIP), 2012 19th IEEE International Conference on. IEEE, 2012.
  18. Ng, Choon-Ching, et al. "Automatic Wrinkle Detection Using Hybrid Hessian Filter." Computer Vision--ACCV 2014. Springer International Publishing, 2015. 609-622.
  19. Ng, Choon-Ching, et al. "Wrinkle detection using hessian line tracking." (2015).
  20. Ng, Choon-Ching, et al. "An Investigation on Local Wrinkle-based Extractor of Age Estimation."
  21. Bando, Yosuke, Takaaki Kuratate, and Tomoyuki Nishita. "A simple method for modeling wrinkles on human skin." Computer Graphics and Applications, 2002. Proceedings. 10th Pacific Conference on. IEEE, 2002.
  22. Hayashi, Jun-ichiro, et al. "Age and gender estimation based on wrinkle texture and color of facial images." Pattern Recognition, 2002. Proceedings. 16th International Conference on. Vol. 1. IEEE, 2002.
Index Terms

Computer Science
Information Sciences

Keywords

Age Classification Face Recognition Face Detection methods Feature Extraction techniques Wrinkle Detection.

Powered by PhDFocusTM