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Reseach Article

Review on Face, Ear and Signature for Human Identification

by Suvarnsing G. Bhable, Sumegh Tharewal, Hanumant Gite, Siddharth Dabhade, K. V. Kale
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 180 - Number 13
Year of Publication: 2018
Authors: Suvarnsing G. Bhable, Sumegh Tharewal, Hanumant Gite, Siddharth Dabhade, K. V. Kale
10.5120/ijca2018916250

Suvarnsing G. Bhable, Sumegh Tharewal, Hanumant Gite, Siddharth Dabhade, K. V. Kale . Review on Face, Ear and Signature for Human Identification. International Journal of Computer Applications. 180, 13 ( Jan 2018), 13-21. DOI=10.5120/ijca2018916250

@article{ 10.5120/ijca2018916250,
author = { Suvarnsing G. Bhable, Sumegh Tharewal, Hanumant Gite, Siddharth Dabhade, K. V. Kale },
title = { Review on Face, Ear and Signature for Human Identification },
journal = { International Journal of Computer Applications },
issue_date = { Jan 2018 },
volume = { 180 },
number = { 13 },
month = { Jan },
year = { 2018 },
issn = { 0975-8887 },
pages = { 13-21 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume180/number13/28921-2018916250/ },
doi = { 10.5120/ijca2018916250 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:00:33.977952+05:30
%A Suvarnsing G. Bhable
%A Sumegh Tharewal
%A Hanumant Gite
%A Siddharth Dabhade
%A K. V. Kale
%T Review on Face, Ear and Signature for Human Identification
%J International Journal of Computer Applications
%@ 0975-8887
%V 180
%N 13
%P 13-21
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Biometrics is a rising technology, which has been extensively used in robotics areas financial services, forensics, secured access, prison security, medical, telecommunication, ecommerce, government, traffic, health care the security issue are more essential. Biometric-based personal identification is high applicability in an extensive range of security application but Multimodal biometrics is the way to reduce time density and give better recognition rate. The concert rate of unimodal biometric is frequently reduced due to the user mode and physiological defects. We have referred papers related to face, ear and signature. In this paper, we discuss different methods of Face, Ear and signature for recognition and identification.

References
  1. R. Raghavendra “Novel mixture model–based approaches for person verification using multimodal biometrics” Springer-Verlag London Limited 2012, pp.1015-1028
  2. Cheng Lu, Jisong Wang, Miao Qi “Multimodal Biometric Identification Approach Based on Face and Palmprint” Second International Symposium on Electronic Commerce and Security IEEE 2009, pp.44-47
  3. Sheetal Chaudhary, Rajender Nath “A Multimodal Biometric Recognition System Based on Fusion of Palmprint, Fingerprint and Face” International Conference on Advances in Recent Technologies in Communication and Computing 2009 pp.596-600
  4. Kyong I. Chang, Kevin W. Bowyer, and Patrick J. Flynn ”An Evaluation of Multimodal 2D+3D Face Biometrics, “ IEEE Transactions On Pattern Analysis And Machine Intelligence, April 2005 , Vol. 27, No. 4, pp.619-924
  5. Teddy Ko “Multimodal Biometric Identification for Large User Population Using Fingerprint, Face and Iris Recognition, “ Proceedings of the 34th Applied Imagery and Pattern Recognition Workshop (AIPR05) IEEE 2005
  6. Muhammad Imran Ahmad, Wai Lok Woo , Satnam Dlay, “Non-stationary feature fusion of face and palmprint multimodal biometrics”, Elsevier Neurocomputing 177 (2016) pp. 49–61
  7. S.M. Mahbubur Rahman , Tamanna Howlader , Dimitrios Hatzinakos ,“On the selection of 2D Krawtchouk moments for face recognition”, Elsevier Pattern Recognition 2016 pp.1-11
  8. M.Pujitha Raj, Manjusha.R, B.Achyut Sarma, S.Vaishnavi, “Multi-modal Biometric system using ear and face (2D+3D) Modalities”, International Journal of Computer Science & Communication Networks ,Vol 5(2), pp.67-71
  9. Xiaona Xu, Zhichun Mu, “Multimodal Recognition Based on Fusion of Ear and Profile Face” Fourth International Conference on Image and Graphics IEEE 2007, pp.598-603
  10. Javier Ortega-Garcia, Julian Fierrez, Fernando Alonso-Fernandez, Javier Galbally, Manuel R. Freire, Gonzalez-Rodriguez, Carmen Garcia-Mateo, Jose-Luis Alba-Castro, Elisardo Gonzalez-Agulla, Enrique Otero-Muras, Sonia Garcia-Salicetti, Lorene Allano, Bao Ly-Van, Bernadette Dorizzi, Josef Kittler, Thirimachos Bourlai, Norman Poh, Farzin Deravi, Ming W.R. Ng, Michael Fairhurst, Jean Hennebert, Andreas Humm, Massimo Tistarelli, Linda Brodo, Jonas Richiardi, Andrzej Drygajlo, Harald Ganster, Federico
  11. Lin Hong and Anil Jain,” Integrating Faces and Fingerprints for Personal Identification”, IEEE Transactions On Pattern Analysis And Machine Intelligence, Vol. 20, No. 12, December 1998, pp. 1295- 1307
  12. Li Yuan, Wei Liu, Yang Li,” Non-negative dictionary based sparse representation classification for ear recognition with occlusion”, Neurocomputing Elsevier 2015, pp.540-550
  13. Asmaa Sabet Anwar, Kareem Kamal A.Ghany, Hesham Elmahdy,” Human Ear Recognition Using Geometrical Features Extraction”, Elsevier International Conference on Communication, Management and Information Technology (ICCMIT 2015), pp. 529 – 537
  14. Francis F. Li,” Sound-Based Multimodal Person Identification from Signature and Voice”, The Fifth International Conference on Internet Monitoring and Protection IEEE 2010, pp.84-88
  15. JuCheng Yang,” Biometrics Verification Techniques Combing with Digital Signature for Multimodal Biometrics Payment System”, International Conference on Management of e-Commerce and e-Government IEEE 2010, pp.405-410
  16. Arn Ross, Anil Jain,” Information fusion in biometrics”, Pattern Recognition Letters 24 Elsevier 2003, pp.2115–2125
  17. Ajay Kumar, Chenye Wu” Automated human identification using ear imaging”, Pattern Recognition in Elsevier 2012, pp. 956–968
  18. Juan Manuel Pascual-Gaspar, Marcos Faundez-Zanuy, Carlos Vivaracho,” Fast on-line signature recognition based on VQ with time modeling”, Engineering Applications of Artificial Intelligence Elsevier 2011, pp. 368–377
  19. Yasmine Serdouk, Hassiba Nemmour, Youcef Chibani,” New offline Handwritten Signature Verification method based on Artificial Immune Recognition System”, Expert Systems With Applications 51 Elsevier (2016) , pp.186–194
  20. K S Radhika, Gopika S” Online and Offline Signature Verification: A Combined Approach”, International Conference on Information and Communication Technologies Elsevier (ICICT 2014), pp. 1593 – 1600
  21. Radhey Shyam, Yogendra Narain Singh, “Identifying Individuals using Multimodal Face Recognition Techniques”, International Conference on Intelligent Computing, Communication & Convergence Elsevier (ICCC-2014), pp. 666 – 672
  22. Ping Yan, Kevin W. Bowyer, “Empirical Evaluation of Ear Biometrics”
  23. Snehlata Barde, A. S. Zadgaonkar, G. R. Sinha, “Multimodal Biometrics using Face, Ear and Iris Modalities”, International Journal of Computer Applications2014, pp.09-15
  24. Md. Maruf Monwar and Marina Gavrilova, “FES: A System for Combining Face, Ear and Signature Biometrics using Rank Level Fusion”, IEEE Fifth International Conference on Information Technology: New Generations 2008. PP 922-927
  25. U. M. Bubeck, and D. Sanchez, “Biometric authentication: Technology & evaluation”, Tech. Report, San Diego State University, USA, 2003.
  26. Sumegh Tharewal,Hanumant Gite,K V Kale,”3D Face and 3D Ear Recognition: Process and Techniques”, (ICCTCEEC) 8 & 9 SEP 2017 Vidyavardhka College of Ebgineering, Mysuru, Karnataka, India.
Index Terms

Computer Science
Information Sciences

Keywords

Face Ear Signature LDA PCA Borda count method Logistic regression method and Rank level Fusion