Open Access   Article Go Back

A Novel Approach to Real Time Face Detection and Recognition

Vikramsingh R. Parihar1 , Anagha P. Dhote2

  1. Prof Ram Meghe College of Engineering and Management, SGBAU, Amravati, India.
  2. Prof Ram Meghe College of Engineering and Management, SGBAU, Amravati, India.

Correspondence should be addressed to: : vikramparihar05@gmail.com.

Section:Research Paper, Product Type: Journal Paper
Volume-5 , Issue-9 , Page no. 62-67, Sep-2017

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v5i9.6267

Online published on Sep 30, 2017

Copyright © Vikramsingh R. Parihar, Anagha P. Dhote . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

View this paper at   Google Scholar | DPI Digital Library

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: Vikramsingh R. Parihar, Anagha P. Dhote, “A Novel Approach to Real Time Face Detection and Recognition,” International Journal of Computer Sciences and Engineering, Vol.5, Issue.9, pp.62-67, 2017.

MLA Style Citation: Vikramsingh R. Parihar, Anagha P. Dhote "A Novel Approach to Real Time Face Detection and Recognition." International Journal of Computer Sciences and Engineering 5.9 (2017): 62-67.

APA Style Citation: Vikramsingh R. Parihar, Anagha P. Dhote, (2017). A Novel Approach to Real Time Face Detection and Recognition. International Journal of Computer Sciences and Engineering, 5(9), 62-67.

BibTex Style Citation:
@article{Parihar_2017,
author = {Vikramsingh R. Parihar, Anagha P. Dhote},
title = {A Novel Approach to Real Time Face Detection and Recognition},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {9 2017},
volume = {5},
Issue = {9},
month = {9},
year = {2017},
issn = {2347-2693},
pages = {62-67},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=1431},
doi = {https://doi.org/10.26438/ijcse/v5i9.6267}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v5i9.6267}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=1431
TI - A Novel Approach to Real Time Face Detection and Recognition
T2 - International Journal of Computer Sciences and Engineering
AU - Vikramsingh R. Parihar, Anagha P. Dhote
PY - 2017
DA - 2017/09/30
PB - IJCSE, Indore, INDIA
SP - 62-67
IS - 9
VL - 5
SN - 2347-2693
ER -

VIEWS PDF XML
916 514 downloads 304 downloads
  
  
           

Abstract

The proposed approach represents novel and simple model approach based on a mixture of techniques and algorithms in a shared pool based on Viola–Jones object detection framework algorithm combined with geometric and symmetric information of the face parts from the image in a smart algorithm. The study is a continued part of previous work, the proposed model is modestly applied with hundreds of face images taken under different lighting conditions, a number of general assumptions used in this research field are identified. The proposed algorithm goes beyond the limits of all existing technologies as it obtains the unique functional features by enabling the proposed model to work with different skin color tone, applying it to low-quality images, detecting faces with eye glasses, determining the position of facial parts (e.g. eye pupils, nose, lips, etc.) and detect several faces on one image is typically designed to deal with single images.

Key-Words / Index Term

Face Detection, Face Recognition, Viola-Jones Algorithm, Object Detection

References

[1] A.Maghraby M.Abdalla O.Enany, “Hybrid Face Detection System using Combination of Viola - Jones Method and Skin Detection”, International Journal of Computer Applications (0975 – 8887) Volume 71– No.6, May 2013
[2] P. Viola and M. J. Jones, “Robust real-time face detection”, International Journal of Computer Vision, 57 (2004), pp. 137–154.
[3] L. Sirovich and M. Meytlis. “Symmetry, probability, and recognition inface space”, PNAS - Proceedings of the National Academy of Sciences,106(17):6895–6899, April 2009.
[4] Fugat Ashlesha G., Gaikwad Shital S., Gangurde Jyoti P. and Sawant Aishwarya S., "A Survey on Secured Online Voting System Using Face Recognition", International Journal of Computer Sciences and Engineering, Vol.3, Issue.9, pp.214-216, 2015.
[5] Prabhjot Singh and Anjana Sharma, "Face Recognition Using Principal Component Analysis in MATLAB", International Journal of Scientific Research in Computer Science and Engineering, Vol.3, Issue.1, pp.1-5, 2015.
[6] Phillip I.W.,Dr. John F. “Facial Feature Detection Using Haar Classifiers”,Jcsc 21, (2006)
[7] Zhang, J., Yan, Y., and Lades, M., “Face Recognition: Eigenfaces, Elas-tic Matching, and Neural Nets”, Proc. IEEE, vol.85, no.9, pp.1423-1435, 1999
[8] Z.H. Zhou and X. Geng, “Projection functions for eye detection”, Pattern Recognition 37, no 5, pp. 1049-1056, 2004
[9] Daugman J (2006) "Probing the uniqueness and randomness of IrisCodes: Results from 200 billion iris pair comparisons." Proceedings of the IEEE, 94(11),
[10] Albiol,A., Albiol,A., Oliver,J., Mossi,J.M.(2012), “Who is who at different cameras: people re- identification using depth cameras”, Computer Vision, IET. Vol 6(5), 378-387.
[11] M. Hassaballah,KenjiMurakami, and Shun Ido, “Eye and Nose Fields Detection From Gray Scale Facial Images”, MVA2011 IAPR Conference on Machine Vision Applications, June 13-15, 2011, Nara, JAPAN
[12] S.Gurumurthy,B.K.Tripathy, “Design and Implementation of Face Recognition System in Matlab Using the Features of Lips”, I.J. Intelligent Systems and Applications,2012,8,30-36.
[13] A.Vora, A.Raj, K.Manikantan, and S.Ramachandran, “Enhanced Face Recognition using 8-Connectivity-of-Skin-Region and Standard- Deviation-based-Pose-Detection as preprocessing techniques”, International Conference on Medical Imaging, m-Health and Emerging Communication Systems,pp.364-369, 2014.
[14] B. Dahal, AbeerAlsadoon, “P.W.C. PrasadandAmrElchouemi, Incorporating Skin Color for Improved Face Detection and Tracking System”, 2016 IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI), pp.-173 – 176, 2016
[15] M. DwisnantoPutro, TeguhBharataAdji, Bondhan Winduratna, “Adult Image Classifiers Based On Face Detection Using Viola-Jones Method”, 2015 1st International Conference on Wireless and Telematics (ICWT), pp. 1-6
[16] Lin, S.-H., Kung, S.Y., and Lin, L.-J., “Face Recognition/ Detection by Probabilistic Decision-Based Neural Network”, IEEE Trans. Neu-ral Networks, vol. 8, No. 1, pp.114-132, Jan. 1997
[17] Chellappa, R., Wilson, C.L., and Sirohey, S., “Human and Machinr Recognition of Faces: A Survey”, Proc. IEEE, vol.83, pp.705-741, May 1995.
[18] Donghe Yang, Jinsong Xia, “Face Tracking Based on CamshiftAlgorithm and Motion Prediction”, International Workshop onIntelligent Systems and Applications, 2009. ISA 2009.
[19] Corporation, “Open Source Computer Vision Library Reference Manual”, 123456-001, 2001.
[20] G. R. Bradski. “Computer vision face tracking for use in a perceptual user interface”, Intel Technology Journal, 2nd Quarter, 1998.
[21] Vikramsingh R. Parihar & Nileshsingh V. Thakur, “Graph Theory Based Approach For Image Segmentation Using Wavelet Transform”, International Journal of Image Processing (IJIP), Volume (8) : Issue (5) : 2014
[22] Vikramsingh R. Parihar, Roshani S. Nage, Atul S. Dahane, “Image Analysis and Image Mining Techniques: A Review”, Journal of Image Processing and Artificial Intelligence, MAT Journals Volume 3 Issue 2, 2017