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A proficient technique for recognizing the online digital signature in Project Registration System (PRS)

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Abstract

In recent education system, project submission is crucial for college students to complete their respective studies. The understudies needed to propose their undertaking before finishing the pre-last year. One of the critical assessment forms like course Project Registration System (PRS) helps the students and their education board to enhance the knowledge and skill level required for competitive world. During project submission, authentication is important to prevent the unauthorized submission of proposal and contrast the signature utilizing classification techniques such as Kernel Based Artificial Neural Network (K-ANN), Kernel Based K-Nearest Neighbor (K-KNN), Kernel Based Self Organizing Map (K-SOM) and Kernel based Support Vector Machine (K-SVM). The data collection based on online digital signature with various students and the proposed classification techniques gives better performance and accuracy compared with other techniques.

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References

  • Batista L, Granger E, Sabourin R (2012) Dynamic selection of generative–discriminative ensembles for off-line signature verification. Pattern Recogn 45(4):1326–1340

    Article  MATH  Google Scholar 

  • Cpałka K, Zalasiński M (2014) On-line signature verification using vertical signature partitioning. Expert Syst Appl 41(9):4170–4180

    Article  Google Scholar 

  • Doroz R, Kudlacik P, Porwik P (2018) Online signature verification modeled by stability oriented reference signatures. Inform Sci. https://doi.org/10.1016/j.ins.2018.05.049

    Article  Google Scholar 

  • Galbally J, Diaz-Cabrera M, Ferrer MA, Gomez-Barrero M, Morales A, Fierrez J (2015) On-line signature recognition through the combination of real dynamic data and synthetically generated static data. Pattern Recogn 48(9):2921–2934

    Article  Google Scholar 

  • Ganorkar PN, and Kalyani P. (2015) Design of digital signature verification algorithm using relative slope method. Int J Res Eng Technol, 1–5

  • Heckeroth J, Dennis Boywitt C (2017) Examining authenticity: an initial exploration of the suitability of handwritten electronic signatures. Forensic Sci Int 275(2017):144–154

    Article  Google Scholar 

  • Houmani N, Mayoue A, Garcia-Salicetti S, Dorizzi B, Khalil MI, Moustafa MN, Abbas H et al (2012) BioSecure signature evaluation campaign (BSEC’2009): evaluating online signature algorithms depending on the quality of signatures. Pattern Recogn 45(3):993–1003

    Article  Google Scholar 

  • Ibrahim MT, Aurangzeb Khan M, Alimgeer KS, Khalid Khan M, Taj IA, Guan L (2010) Velocity and pressure-based partitions of horizontal and vertical trajectories for on-line signature verification. Pattern Recognit 43(8):2817–2832

    Article  MATH  Google Scholar 

  • Rabotka V, Mannan M (2016) An evaluation of recent secure deduplication proposals. J Inform Secur Appl 27:3–18

    Google Scholar 

  • Rashidi S, Fallah A, Towhidkhah F (2013) Similarity evaluation of online signatures based on modified dynamic time warping. Appl Artif Intell 27(7):599–617

    Article  Google Scholar 

  • Sae-Bae N, Memon N, Sooraksa P (2012) Distinctiveness, complexity, and repeatability of online signature templates. Pattern Recogn 84:332–344

    Article  Google Scholar 

  • Shankar TN, Sahoo G, Niranjan S (2012) Using the digital signature of a fingerprint by an elliptic curve cryptosystem for enhanced authentication. Inform Secur J Glob Perspect 21(5):243–255

    Article  Google Scholar 

  • Shankar TN, Sahoo G, Niranjan S (2012) Using the digital signature of a fingerprint by an elliptic curve cryptosystem for enhanced authentication. Inform Secur J Glob Perspect 21(5):243–255

    Article  Google Scholar 

  • Vélez J, Sánchez Á, Moreno B, Esteban JL (2009) Fuzzy shape-memory snakes for the automatic off-line signature verification problem. Fuzzy Sets Syst 160(2):182–197

    Article  Google Scholar 

  • Yasuda K, Muramatsu D, Shirato S, Matsumoto T (2010) Visual-based online signature verification using features extracted from video. J Netw Comput Appl 33(3):333–341

    Article  Google Scholar 

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Authors and Affiliations

  1. Information Technology, University of Technology and Applied Sciences Al Mussanah (UTASA), Muladdah, Sultanate of Oman

    R. Ravi Chakravarthi

  2. Electronics and Communication Engineering, Teegala Krishna Reddy Engineering College, Hyderabad, India

    C. Anna Palagan

  3. Computer Science, University of Nizwa, Nizwa, Sultanate of Oman

    Ravindra Ratilal Dharamshi

  4. Computer Science and Engineering, Teegala Krishna Reddy Engineering College, Hyderabad, India

    N. Vadivelan

  5. Business Studies, University of Technology and Applied Sciences Al Mussanah (UTASA), Muladdah, Sultanate of Oman

    Shrikant Taware

Authors
  1. R. Ravi Chakravarthi
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  2. C. Anna Palagan
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  3. Ravindra Ratilal Dharamshi
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  4. N. Vadivelan
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  5. Shrikant Taware
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Corresponding author

Correspondence to R. Ravi Chakravarthi.

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The authors declare that they have no conflict of interest. This article does not contain any studies with human participants or animals performed by any of the authors.

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Communicated by Meng Joo.

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Ravi Chakravarthi, R., Anna Palagan, C., Dharamshi, R.R. et al. A proficient technique for recognizing the online digital signature in Project Registration System (PRS). Soft Comput 27, 1673–1684 (2023). https://doi.org/10.1007/s00500-022-07071-2

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  • DOI: https://doi.org/10.1007/s00500-022-07071-2

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