Skip to main content

Analytical Study of Edge Detection Algorithms and Contouring Algorithm

  • Chapter
  • First Online:
Dental Image Processing for Human Identification

Abstract

This chapter presents an analytical study of various edge detection algorithms and its usefulness in biometric recognition. This chapter also covers relevant information about contouring algorithm and how its value can be calculated.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 79.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 99.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Bibliography

  1. Pithadiya, K., Modi, C. K., Chauhan, J. D., & Jain, K. R. (2009). Performance evaluation of ISEF and Canny edge detector in acrylic fibre quality control production. In Proceedings of National conference on innovations in Mechatronics. IME.

    Google Scholar 

  2. Weber, A. G. (1997). The USC-SIPI image database version 5. USC-SIPI Report, 315, 1–24.

    Google Scholar 

  3. Canny, J. (1987). A computational approach to edge detection. In Readings in computer vision (pp. 184–203).

    Google Scholar 

  4. Rong, W., Li, Z., Zhang, W., & Sun, L. (2014). An improved CANNY edge detection algorithm. In Mechatronics and Automation (ICMA), 2014 IEEE International Conference on (pp. 577–582). IEEE.

    Google Scholar 

  5. Shen, J., & Castan, S. (1988). Edge detection based on multi-edge models. In Real-time image processing: Concepts and technologies (Vol. 860, pp. 46–54). International Society for Optics and Photonics.

    Google Scholar 

  6. Purushotham, S., & Anouncia, M. (2009). Enhanced human identification system using dental biometrics. In Proceedings of the 10th WSEAS International Conference on NEURAL NETWORKS (pp. 120–125). World Scientific and Engineering Academy and Society (WSEAS).

    Google Scholar 

  7. Sandberg, B., Chan, T., & Vese, L. (2002). A level-set and Gabor-based active contour algorithm for segmenting textured images. In UCLA Department of Mathematics CAM report.

    Google Scholar 

  8. Meng, X., Nandagopal, T., Li, L., & Lu, S. (2006). Contour maps: Monitoring and diagnosis in sensor networks. Computer Networks, 50(15), 2820–2838.

    Article  Google Scholar 

  9. Lefkowitz, H. M. (2000). U.S. Patent No. 6,091,417. Washington, DC: U.S. Patent and Trademark Office.

    Google Scholar 

  10. Moore, H. (2017). MATLAB for engineers. New York, US: Pearson.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Trivedi, D.N., Shah, N.D., Kothari, A.M., Thanki, R.M. (2019). Analytical Study of Edge Detection Algorithms and Contouring Algorithm. In: Dental Image Processing for Human Identification. Springer, Cham. https://doi.org/10.1007/978-3-319-99471-0_3

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-99471-0_3

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-99470-3

  • Online ISBN: 978-3-319-99471-0

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics