Call for Paper - March 2023 Edition
IJCA solicits original research papers for the March 2023 Edition. Last date of manuscript submission is February 20, 2023. Read More

Age Group Estimation by Combining Texture and Fractal Analysis

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
N.K.Bansode, P.K. Sinha

N.K.Bansode and P K Sinha. Article: Age Group Estimation by Combining Texture and Fractal Analysis. International Journal of Computer Applications 139(13):29-33, April 2016. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

	author = {N.K.Bansode and P.K. Sinha},
	title = {Article: Age Group Estimation by Combining Texture and Fractal Analysis},
	journal = {International Journal of Computer Applications},
	year = {2016},
	volume = {139},
	number = {13},
	pages = {29-33},
	month = {April},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}


In this paper the age group estimation is presented based on combination of texture and fractal dimension features. The age of the human is used as one of the important key parameter for computer vision applications. The fractal dimension of the face image and the texture analysis is used to classify the age of the person into the three different groups such as child(10-20), young(21-50) and old(51 and above. The proposed approach of combing the fractal and texture features shows an effective estimation of the age group. The facial age groups are estimated with 90% average accuracy.


  1. Jian Li, QianDu, CaixinSun, “An improved box-counting method for image fractal dimension estimation”, Pattern Recognition 42 (2009) 2460 - 2469
  2. Ruoyu Du, Hyo Jong Lee, “ Consistency of Optimized Facial Features through the Ages”, International Journal of Multimedia and Ubiquitous Engineering Vol.8, No.5 (2013), pp.61-70
  3. Kung-Yu Chang , Chusong Chen ,Yi Ping Hung, “A ranking approach for human age estimation based on face images” IEEE International Conference on Pattern Recognition 2010
  4. Rishi Gupta ,Dr. Ajay khunteta, “SVM Age classify based on the facial images” Intentional journal of computing communications and networking Vol.1 No 2 Oct 2012 .
  5. Dong Cao, Zhen Lei, Zhiwei Zhang, Jun Feng, Stan Z. Li, “Human age estimation using ranking SVM “
  6. Khoa Luu Karl Ricanek, Tien D.Bui Ching Y. Suen ,”Age estimation using active appearance models and support vector machine Regression” ,IEEE 2009
  7. Mohamed Y.Ei Dib Hoda M.Onsi, “Human age estimation framework using different Facial parts”, Egyptian Informatics Journal 2011, Cairo
  8. Mohammad Mahdi Deshidi Azam Bastanfard, “A new algorithm for age recognition from facial images”, Signal Processing Elsevier Journal 2010, 2431-2444
  9. Catherine M. Scandrett( Nee Hill) , Christopher J. Solomon, Stuart J.Gibson ,“A Person –Specific, Rigorous Aging Model Of The Human Face”, Elsevier Journal Pattern Recognition Letters 2006, 1776-1787
  10. Ranjan Jana, Debaleena Datta, Rituparna Saha, “Age group estimation using face features” , International Journal of Engineering and Innovative Technology (IJEIT) Vol. 2 Issue 2, August 2013 ISSN 2277-3754.
  11. Wen-Bing Horng Cheng-Ping Lee And Chun Wen Chen , “Classification of age groups based on facial features”, Tamkang Journal of Science and Engineering Vol. 4 No.3 pp. 183-192(2001).
  12. Gayathri Mahalingam , Chandra kambhamettu ,”Face Verification With Aging Using Adaboost And Local Binary Patterns”, ICVGIP’10 Dec 12-15 2010 Chennai ,India.
  13. H. Kwon Young And Niels Da Vitoria Lobo ,”Age Classification From Facial Images”, Computer vision and Image Understanding Vol. 74 No 1 April 1999 pp. 1-21.
  14. Sung Eun, Choi Youn,Juo Lee, Sung joo Lee, Kang Ryoung ,Fark Jaihie Kim, “Age Estimation Using A Hierarchical Classifier Based On Global And Local Facial Features” l Elsevier Journal Pattern Recognition 1262-1281,2011.
  15. Dihong Gong ,Zhifeng Li ,dahua Lin, Jianzhuang Liu, Xiaoou Tang. “Hidden Factor Analysis for Age Invariant Face Recognition”, ICCV2013.
  16. Milan Sonka, Vaclav Halvac, Roger Boyle, Image Processing, Analysis and Machine Vision pp646 -656
  17. Lucas Correia Ribas Diogo Nunes Goncalves , Joratan Patrik Margarido Orue, “Fractal dimension of maximum response filters applied to texture analysis’, Pattern Recognition Letters(2015) 116-123
  18. Rajendra Babu, E Sreenivasa Reddy,B Prabhakar Rao,” Age Group classification of facial images using Rank based Edge Texture Unit”, Procedia Computer Science 45(2015)
  22. Refael C Gonzalez, Richard E Woods, Steven L Eddins, “Digital Image Processing”, pp. 441-450


Texture Features , Fractals, Age Group