A Novel Secure Personal Authentication System with Finger in Face Watermarking Mechanism

  • Chinta Someswara Rao
  • K. V. S. Murthy
  • R. Shiva Shankar
  • V. Mnssvkr Gupta
Part of the Studies in Computational Intelligence book series (SCI, volume 730)


Facial and Finger authentication plays a pivotal role for proving personal verification in any organization, industry, enterprise, etc. In the previous works, authentication systems are developed by using the password, pin number, digital signature, etc., as a single source of identification. But all these systems can be subjected to spoofing attack. In this paper, a novel authentication system is proposed with image-in-image Fast Hadmard Transform (FHT) watermarking and authentication with Singular Value Decomposition (SVD). The proposed system is strong enough from attacks as the authentication is being done using face and finger traits. The proposed work is useful for reducing the size of the database, identification and authentication for bank systems, crime investigations, organizational attendance systems, and for knowing student attendance system, unauthorized copying, etc.


Face Finger Authentication Personal verification FHT SVD 


  1. 1.
    Wu, M., Chen, J., Zhu, W., Yuan, Z.: Security analysis and enhancements of a multi-factor biometric authentication scheme. Int. J. Electron. Secur. Digit. Forensics 352–365 (2016)Google Scholar
  2. 2.
    Sheth, R.K., Nath, V.V.: Secured digital image watermarking with discrete cosine transform and discrete wavelet transform method. In: International Conference on Advances in Computing, Communication, and Automation, pp. 1–5 (2016)Google Scholar
  3. 3.
    Al-Haj, A., Hussein, N., Abandah, G.: Combining cryptography and digital watermarking for secured transmission of medical images. In: International Conference on Information Management, pp. 40–46 (2016)Google Scholar
  4. 4.
    Al-Haj, A., Mohammad, A.: Crypto-watermarking of transmitted medical images. J. Digit. Imaging 1–3 (2016)Google Scholar
  5. 5.
    Mallick, A.K., Maheshkar, S.: Digital image watermarking scheme based on visual cryptography and SVD. In: International Conference on Frontiers in Intelligent Computing: Theory and Applications, pp. 589–598 (2015)Google Scholar
  6. 6.
    Kumar, S., Dutta, A.: A novel spatial domain technique for digital image watermarking using block entropy. In: International Conference on Recent Trends in Information Technology, pp. 1–4 (2016)Google Scholar
  7. 7.
    Joshi, A.M., Bapna, M., Meena, M.: Blind image watermarking of variable block size for copyright protection. In: International Conference on Recent Cognizance in Wireless Communication and Image Processing, pp. 853–859 (2016)Google Scholar
  8. 8.
    Vellasques, E., Sabourin, R., Granger, E.: A dual-purpose memory approach for dynamic particle swarm optimization of recurrent problems. In: Recent Advances in Computational Intelligence in Defense and Security, pp. 367–389 (2016)Google Scholar
  9. 9.
    Hua, G., Huang, J., Shi, Y.Q., Goh, J., Thing, V.L.: Twenty years of digital audio watermarking—a comprehensive review. Signal Process. 222–242 (2016)Google Scholar
  10. 10.
    Seitz, J.: Digital Watermarking for Digital Media. Information Science Publishing (2004)Google Scholar
  11. 11.
    Bas, P., Furon, T., Cayre, F., Doërr, G., Mathon, B.: A quick tour of watermarking techniques. In: Security in Watermarking, pp. 13–31 (2016)Google Scholar
  12. 12.
    Dragoi, I.C., Coltuc, D.: A simple four-stages reversible watermarking scheme. In: International Symposium on in Signals, Circuits and Systems, pp. 1–4 (2015)Google Scholar
  13. 13.
    Xiang, S., Wang, Y.: Non-integer expansion embedding techniques for reversible image watermarking. J. Adv. Signal Process. 1–2 (2015)Google Scholar
  14. 14.
    Ghosh, S., De, S., Maity, S.P., Rahaman, H.: A novel dual purpose spatial domain algorithm for digital image watermarking and cryptography using Extended Hamming Code. In: International Conference on Electrical Information and Communication Technology, pp. 167–172 (2015)Google Scholar
  15. 15.
    Zhou, Q., Lu, S., Zhang, Z., Sun, J.: Quantum differential cryptanalysis. Quantum Inf. Process. 2101–2109 (2015)Google Scholar
  16. 16.
    Van Schyndel, R.G., Tirkel, A.Z., Osborne, C.F.:A digital watermark. In: International Conference on Image Processing, pp. 86–90 (1994)Google Scholar
  17. 17.
    Van Schyndel, R.G., Tirkel, A.Z., Svalbe, ID.: Key independent watermark detection. In: International Conference on Multimedia Computing and Systems, pp. 580–585 (1999)Google Scholar
  18. 18.
    Huang, P.S., Chiang, C.S., Chang, C.P., Tu. T.M.: Robust spatial watermarking technique for colour images via direct saturation adjustment. In: IEE Proceedings-Vision, Image and Signal Processing, pp. 561–574 (2005)Google Scholar
  19. 19.
    Zhu, X., Zhao, J., Xu, H.: A digital watermarking algorithm and implementation based on improved SVD. In: International Conference on Pattern Recognition, pp. 651–656 (2006)Google Scholar
  20. 20.
    Liang, L., Qi, S.: A new SVD-DWT composite watermarking. In: International Conference on Signal Processing 2006Google Scholar
  21. 21.
    Ali, M., Ahn, C.W., Pant, M.: A robust image watermarking technique using SVD and differential evolution in DCT domain. Optik-Int. J. Light Electron Opt. 428–434 (2014)Google Scholar
  22. 22.
    Bors, A.G., Pitas, I.: Image watermarking using DCT domain constraints. In: International Conference on Image Processing, pp. 231–234 (1996)Google Scholar
  23. 23.
    Hernandez, J.R., Amado, M., Perez-Gonzalez, F.: DCT-domain watermarking techniques for still images: detector performance analysis and a new structure. IEEE Trans. Image Process. 55–68 (2000)Google Scholar
  24. 24.
    Lu, C.S., Chen, J.R., Liao, H.Y., Fan, K.C.: Real-time MPEG2 video watermarking in the VLC domain. In: International Conference on Pattern Recognition, pp. 552–555 (2002)Google Scholar
  25. 25.
    Mohanty, S.P., Ranganathan, N., Balakrishnan, K.: A dual voltage-frequency VLSI chip for image watermarking in DCT domain. IEEE Trans. Circuits Syst. II: Express Briefs 394–398 (2006)Google Scholar
  26. 26.
    Amini, M., Ahmad, M., Swamy, M.: A robust multibit multiplicative watermark decoder using vector-based hidden Markov model in wavelet domain. IEEE Trans. Circuits Syst. Video Technol. (2016)Google Scholar
  27. 27.
    Wei, C., Zhaodan, L.: Robust watermarking algorithm of color image based on DWT-DCT and chaotic system. In: International Conference on Computer Communication and the Internet, pp. 370–373 (2016)Google Scholar
  28. 28.
    Lu, Z.M., Guo, S.Z.: Lossless Information Hiding in Images. Syngress (2016)Google Scholar
  29. 29.
    Lu, C.S., Huang, S.K., Sze, C.J., Liao, H.Y.: Cocktail watermarking for digital image protection. IEEE Trans. Multimedia 209–224 (2000)Google Scholar
  30. 30.
    Hua, L.I., Xi, Z.G., Ting, Z.Y.: A visual model weighted image watermarking method using wavelet decomposition. J. China Inst. 006 (2000)Google Scholar
  31. 31.
    Voyatzis, G., Pitas, I.: Applications of toral automorphisms in image watermarking. In: International Conference on Image Processing, pp. 237–240 (1996)Google Scholar
  32. 32.
    El-Taweel, G.S., Onsi, H.M., Samy, M., Darwish, M.G.: Secure and non-blind watermarking scheme for color images based on DWT. ICGST Int. J. Graph. Vis. Image Process. 15 (2005)Google Scholar
  33. 33.
    Xia, X.-G., Boncelet, C.G., Arce, G.R.: A multiresolution watermark for digital images. In: International Conference on Image Processing, pp. 548–551 (1997)Google Scholar
  34. 34.
    Raval, M.S., Rege, P.P.: Discrete wavelet transform based multiple watermarking scheme. In: International Conference on Convergent Technologies for the Asia-Pacific Region, pp. 935–938 (2003)Google Scholar
  35. 35.
    Kundur, D., Hatzinakos, D.: Digital watermarking using multiresolution wavelet decomposition. In: International Conference on Acoustics, Speech and Signal Processing, pp. 2969–2972 (1998)Google Scholar
  36. 36.
    Tao, P., Eskicioglu, A.M.: A robust multiple watermarking scheme in the discrete wavelet transform domain. Int. Soc. Opt. Photonics 133–144 (2004)Google Scholar
  37. 37.
    Dong, J., Li, J.: A robust zero-watermarking algorithm for encrypted medical images in the DWT-DFT encrypted domain. Innov. Med. Healthc. 197–208 (2016)Google Scholar
  38. 38.
    Kang, X., Huang, J., Shi, Y.Q., Lin, Y.: A DWT-DFT composite watermarking scheme robust to both affine transform and JPEG compression. IEEE Trans. Circuits Syst. Video Technol. 776–786 (2003)Google Scholar
  39. 39.
    Solachidis, V., Pitas, L.: Circularly symmetric watermark embedding in 2-D DFT domain. IEEE Trans. Image Process. 1741–1753 (2001)Google Scholar
  40. 40.
    Ganic, E., Eskicioglu, A.M.: Robust DWT-SVD domain image watermarking: embedding data in all frequencies. In: Workshop on Multimedia and Security, pp. 166–174 (2004)Google Scholar
  41. 41.
    Pereira, S., Pun, T.: Robust template matching for affine resistant image watermarks. IEEE Trans. Image Process. 1123–1129 (2000)Google Scholar
  42. 42.
    Falkowski, B.J., Lim, L.S.: Image watermarking using Hadamard transforms. Electron. Lett. 211–213 (2000)Google Scholar
  43. 43.
    Gilani, S.A., Kostopoulos, I., Skodras, A.N.: Color image-adaptive watermarking. In: International Conference on Digital Signal Processing, pp. 721–724 (2002)Google Scholar
  44. 44.
    Kaur, A., Dutta, M.K., Burget, R., Riha, K.: A heuristic algorithmic approach to challenging robustness of digital audio watermarking using discrete wavelet transform”, International Conference on Telecommunications and Signal Processing, pp. 519–522, 2016Google Scholar
  45. 45.
    Shao, Y., Wu, G., Lin, X.: Quantization-based digital watermarking algorithm. J. Tsinghua Univ. 006 (2003)Google Scholar
  46. 46.
    Bose, A., Maity, S.P.: Improved spread spectrum compressive image watermark detection with distortion minimization. In: International Conference on Signal Processing and Communications, pp. 1–5 (2016)Google Scholar
  47. 47.
    Xiao, J., Wang, Y.: Toward a better understanding of DCT coefficients in watermarking. In: Pacific-Asia Workshop on Computational Intelligence and Industrial Application, pp. 206–209 (2008)Google Scholar
  48. 48.
    You, J., Li, W., Zhang, D.: Hierarchical palmprint identification via multiple feature extraction. Pattern Recogn. 847–859 (2002)Google Scholar
  49. 49.
    Holt, S.B.: Finger‐print patterns in mongolism. Ann. Hum. Genet. 279–282 (1963)Google Scholar
  50. 50.
    Zhao, Q., Zhang, L., Zhang, D., Luo, N.: Adaptive pore model for fingerprint pore extraction. Proc. IEEE (2008)Google Scholar
  51. 51.
    Girgis, M.R., Mahmoud, T.M., Abd-El-Hafeez, T.: An approach to image extraction and accurate skin detection from web pages. World Acad. Sci. Eng. Technol. 27 (2007)Google Scholar
  52. 52.
    Kaur, M., Singh, M., Girdhar, A., Sandhu, P.S.: Fingerprint verification system using minutiae extraction technique. World Acad. Sci. Eng. Technol. 46 (2008)Google Scholar
  53. 53.
    Le, H., Bui, T.D.: Online fingerprint identification with a fast and distortion tolerant hashing. J. Inf. Assur. Secur. 117–123 (2009)Google Scholar
  54. 54.
    Ratha, N.K., Karu, K., Chen, S., Jain, A.K.: A real-time matching system for large fingerprint databases. Trans. Pattern Anal. Mach. Intell. 799–813 (1996)Google Scholar
  55. 55.
    Jain, A., Chen, Y., Demirkus, M.: Pores and ridges: fingerprint matching using level 3 features. Pattern Recogn. Lett. 2221–2224 (2004)Google Scholar
  56. 56.
    Vatsa, M., Singh, R., Noore, A., Singh, S.K.: Combining pores and ridges with minutiae for improved fingerprint verification. Signal Process. 2676–2685 (2009)Google Scholar
  57. 57.
    Uludaga, U., Ross, A., Jain, A.: Biometric template selection and update: a case study in fingerprints. Pattern Recogn. 1533–1542 (2004)Google Scholar
  58. 58.
    Coetzee, L., Botha, E.C.: Fingerprint recognition in low quality images. Pattern Recogn. (1993)Google Scholar
  59. 59.
    O‟Gormann, L., Nickerson, J.V.: An approach to fingerprint filter design. Pattern Recogn. 29–38 (1989)Google Scholar
  60. 60.
    Yuan, W., Lixiu, Y., Fuqiang, Z.: A real time fingerprint recognition system based on novel fingerprint matching strategy. In: International Conference on Electronic Measurement and Instruments (2007)Google Scholar
  61. 61.
    Cui, W., Wu, G., Hua, R., Yang, H.: The research of edge detection algorithm for fingerprint images. Proc. IEEE (2008)Google Scholar
  62. 62.
    Li, S., Wei, M., Tang, H., Zhuang, T., Buonocore, M.H.: Image enhancement method for fingerprint recognition system. In: Annual Conference on Engineering in Medicine and Biology, pp. 3386–3389 (2005)Google Scholar
  63. 63.
    Mil’shtein, S., Pillai, A., Shendye, A., Liessner, C., Baier, M.: Fingerprint recognition algorithms for partial and full fingerprints. Proc. IEEE (2008)Google Scholar
  64. 64.
    Ross, A., Uludag, U., Jain, A.: Biometric template selection and update: a case study in fingerprints. Pattern Recogn. Soc. (2003)Google Scholar
  65. 65.
    Karna, D.K., Agarwal, S., Nikam, S.: Normalized cross-correlation based fingerprint matching. In: Fifth International Conference on Computer Graphics, Imaging and Visualization (2008)Google Scholar
  66. 66.
    Bazen, A.M., Verwaaijen, G.T.B., Gerez, S.H.: A correlation-based fingerprint verification system. In: Workshop on Circuits, Systems and Signal Processing, Veldhoven (2000)Google Scholar
  67. 67.
    Lowe, D.G.: Distinctive image features from scale-invariant key points. Int. J. Comput. Vis. (2004)Google Scholar
  68. 68.
    Schalkoff, R.J.: Digital Image Processing and Computer Vision. Wiley Publications, New York (1989)Google Scholar
  69. 69.
    Saryazdi, S., Nezamabadi-Pour, H.: A blind digital watermark in Hadamard domain. World Acad. Sci. Eng. Technol. 126–129 (2005)Google Scholar
  70. 70.
    Rao, C.S., Murthy, K.V., Gupta, V.M., Raju, G.P., Raju, S.V., Balakrishna, A.: Implementation of object oriented approach for copyright protection using Hadamard transforms. In: International Conference on Computer and Communication Technology, pp. 473–480 (2010)Google Scholar
  71. 71.
    Devi, B.P., Singh, K.M., Roy, S.: A Copyright Protection Scheme for Digital Images Based on Shuffled Singular Value Decomposition and Visual Cryptography, p. 1091. Springer Plus (2016)Google Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Chinta Someswara Rao
    • 1
  • K. V. S. Murthy
    • 1
  • R. Shiva Shankar
    • 1
  • V. Mnssvkr Gupta
    • 1
  1. 1.Department of CSES.R.K.R Engineering CollegeW.G. District, BhimavaramIndia

Personalised recommendations