A preliminary study and its application for the development of the quantitative evaluation method of developed fingerprints on porous surfaces using densitometric image analysis

다공성 표면에서 현출된 지문의 정량적인 평가방법 개발을 위한 농도계 이미지 분석을 이용한 선행연구 및 응용

  • Cho, Jae-Hyun (Department of Scientific Criminal Investigation, Chungnam National University) ;
  • Kim, Hyo-Won (Department of Scientific Criminal Investigation, Chungnam National University) ;
  • Kim, Min-Sun (Department of Scientific Criminal Investigation, Chungnam National University) ;
  • Choi, Sung-Woon (Graduate School of New Drug Discovery and Development, Chungnam National University)
  • 조재현 (충남대학교 평화안보대학원 과학수사학과) ;
  • 김효원 (충남대학교 평화안보대학원 과학수사학과) ;
  • 김민선 (충남대학교 평화안보대학원 과학수사학과) ;
  • 최성운 (충남대학교 신약전문대학원 신약개발학과)
  • Received : 2016.04.17
  • Accepted : 2016.06.13
  • Published : 2016.06.25


In crime scene investigation, fingerprint identification is regarded to be one of the most important techniques for personal identification. However, objective and unbiased evaluation methods that would compare the fingerprints with diverse available and developing methods are currently lacking. To develop an objective and quantitative method to improve fingerprint evaluation, a preliminary study was performed to extract useful research information from the analysis with densitometric image analysis (CP Atlas 2.0) and the Automated Fingerprint Identification System (AFIS) for the developed fingerprints on porous surfaces. First, inked fingerprints obtained by varying pressure (kg.f) and pressing time (sec.) to find optimal conditions for obtaining fingerprint samples were analyzed, because they could provide fingerprints of a relatively uniform quality. The extracted number of minutiae from the analysis with AFIS was compared with the calculated areas of friction ridge peaks from the image analysis. Inked fingerprints with a pressing pressure of 1.0 kg.f for 5 seconds provided the most visually clear fingerprints, the highest number of minutiae points, and the largest average area of the peaks of the friction ridge. In addition, the images of the developed latent fingerprints on thermal paper with the iodine fuming method were analyzed. Fingerprinting condition of 1.0 kg.f/5 sec was also found to be optimal when generating highest minutiae number and the largest average area of peaks of ridges. Additionally, when the concentration of ninhydrin solution (0.5 % vs. 5 %) was used to compare the developed latent fingerprints on print paper, the best fingerprinting condition was 2.0 kg.f/5 sec and 5 % of ninhydrin concentration. It was confirmed that the larger the average area of the peaks generated by the image analysis, the higher the number of minutiae points was found. With additional tests for fingerprint evaluation using the densitometric image analysis, this method can prove to be a new quantitative and objective assessment method for fingerprint development.


latent fingerprint;fingerprint evaluation;densitometric image analysis;AFIS


  1. S. H. James, J. J. Nordby and S. Bel, In ‘Forensic Science’, 3rd Ed., p303-326, CRC Press, USA, 2014.
  2. P. R. De Forest, R. E. Gaensslen and H. C. Lee, ‘Forensic science: an introduction to criminalistics’, McGraw-Hil, New York, USA, 1983.
  3. S. H. James, J. J. Nordby and S. Bel, In ‘Forensic Science’, 3rd Ed., p355-375, CRC Press, USA, 2014.
  4. S. L. Zabell, JL & Pol’y., 13(143), 143-179 (2005).
  5. H. L. Bandey and A. P. Gibson (2006), The powders process, study 2: Evaluation of fingerprint powders on smooth surfaces. HOSDB Fingerprint Development and Imaging Newsletter 08/06: 7.
  6. J. W. Bond, J. Forensic Sci., 59(2), 485-489 (2014).
  7. R. Bansal, P. Sehgal and P. Bedi, Int. J. of Computer Sci., 8(5), 74-85 (2011).
  8. S. Jovanovic, M. Barac, O. Macej, T. Vucic and C Lacnjevac, Sensors, 7(3), 371-383 (2007).
  9. J. H. Cho, 'A Preliminary Study for the Development of the Quantitative Evaluation Method of Developed Fingerprints Using Densitometric Image Analysis and its Application', Master's thesis, Chungnam National University, Daejeon, 2016.
  10. O. P. Jasuja and G. Singh, Forensic Sci. Int., 192(1), e11-e16 (2009).
  11. P. F. Kelly, R. S. P. King, S. M. Bleay and T. O. Daniel, Forensic Sci. Int., 217(1), e27-e30 (2012).
  12. H. C. Lee and R. E. Gaensslen, ‘Advances in Fingerprint Technology’, 2nd Ed., 105-176, CRC Press, USA, 2001.
  13. J. S. Yu, J. S. Jung, S. Lim and S. W. Park, Anal. Sci. Technol., 25(3), 164-170 (2012).
  14. O. P. Jasuja, M. A. Toofany, G. Singh and G. S. Sodhi, Sci. Justice, 49(1), 8-11 (2009).
  15. M. K. Kim, S. W. Park and Y. Ohgami, Anal. Sci. Technol., 22(2), 166-171 (2009).
  16. Y. S. Kim and S. W. Choi, Korean J. Sci. Crim. Invest., 7(4), 272-278 (2013).
  17. J. Almog, A. Hirshfeld and J. T. Klug, J. Forensic Sci., 27(4), 912-917 (1982).

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