Advertisement

Novel Technological Applications for Latent and Blood-Stained Fingermark Aging Studies

  • Josep De Alcaraz-FossoulEmail author
  • Meez Islam
Chapter
Part of the Advanced Sciences and Technologies for Security Applications book series (ASTSA)

Abstract

At the present time, there are no standard methodologies to reliably determine the age of (latent) fingermarks recovered from crime scenes. Estimating the time of deposition of this type of evidence is a complex challenge that remains scientifically unsolved in the forensic domain. This chapter addresses the effort to investigate and evaluate the age of fingermarks, and answer the question: how much information can “imaging technologies” provide on fingermark aging? The objective is to introduce the reader to novel applications of existing technologies—Optical Profilometry (OP) and visible wavelength Hyperspectral Imaging (HSI)—that can visualize and record variations in the topography of ridges and follow spectral changes in blood-stained fingermarks, respectively. OP has been typically used for the 3D analysis of surface roughness of materials; whereas HSI has been previously used to detect and identify blood stains in a forensic context and estimate their age in laboratory settings. These non-destructive, contactless, imaging technologies eliminate the need for manipulating friction ridge skin impressions and minimizing sample destruction. Most importantly, they allow the simultaneous collection of qualitative and quantitative data that can be analyzed using spatio-temporal statistical models to investigate the mechanisms involved in ridge degradation. OP and HSI, among other technologies, are establishing new foundational research to integrate the age variable in future fingermark examination flowcharts. This inclusion could potentially reduce identification errors that are caused by time inconsistencies between the evidence discovered and the crime committed, as well as maximize the use of resources by decreasing the number of traces to be processed.

Notes

Acknowledgements

Prof. M. Islam would like to thank Dr. Samuel Cadd, Dr. Bo Li and colleagues at Chemicam Ltd. for the HSI research and results described in this chapter.

Dr. J. De Alcaraz-Fossoul would like to thank Dr. Emmanuel Soignard, Dr. Michelle Mancenido, Dr. Carme Barrot Feixat, Dr. Sara C. Zapico, Ms. Lindsey Porter and all collaborators at Arizona State University, the University of Barcelona, California State University—Los Angeles, Forensic Focus Ltd. and the Catalonia PoliceMossos d’Esquada who have contributed, in part, to the research presented.

References

  1. 1.
    Girod A, Ramotowski R, Weyermann C (2012) Composition of fingermark residue: a qualitative and quantitative review. Forensic Sci Int 223(1–3):10–24PubMedCrossRefGoogle Scholar
  2. 2.
    Ng PHR et al (2009) Detection of illicit substances in fingerprints by infrared spectral imaging. Anal Bioanal Chem 394(8):2039–2048PubMedCrossRefGoogle Scholar
  3. 3.
    Rowell F, Hudson K, Seviour J (2009) Detection of drugs and their metabolites in dusted latent fingermarks by mass spectrometry. Analyst 134(4):701–707PubMedCrossRefGoogle Scholar
  4. 4.
    Wertheim K (2003) Fingerprint age determination: is there any hope? J Forensic Ident 53(1):42–49Google Scholar
  5. 5.
    Girod A, Ramotowski R, Lambrechts S, Misrielal P, Aalders M, Weyermann C (2016) Fingermark age determinations: Legal considerations, review of the literature and practical propositions. Forensic Sci Int 262:212–226PubMedCrossRefGoogle Scholar
  6. 6.
    Archer NE, Charles Y, Elliott J, Jickells S (2005) Changes in the lipid composition of latent fingerprint residue with time after deposition on a surface. Forensic Sci Int 154(2–3):224–239PubMedCrossRefGoogle Scholar
  7. 7.
    Humphreys JD, Porter G, Bell M (2008) The quantification of fingerprint quality using a relative contrast index. Forensic Sci Int 178(1):46–53PubMedCrossRefGoogle Scholar
  8. 8.
    Croxton RS, Baron MG, Butler D, Kent T, Sears VG (2010) Variation in amino acid and lipid composition of latent fingerprints. Forensic Sci Int 199(1–3):93–102PubMedCrossRefGoogle Scholar
  9. 9.
    Weyermann C, Roux C, Champod C (2011) Initial results on the composition of fingerprints and its evolution as a function of time by GC/MS analysis. J Forensic Sci 56(1):102–108PubMedCrossRefGoogle Scholar
  10. 10.
    Merkel R, Gruhn S, Dittmann J, Vielhauer C, Brautigam A (2012) On non-invasive 2D and 3D chromatic white light image sensors for age determination of latent fingerprints. Forensic Sci Int 222:52–70PubMedCrossRefGoogle Scholar
  11. 11.
    Bailey MJ, Bright RS, Croxton S, Francese LS, Ferguson S, Hinder S, Jickells BJ, Jones BN, Jones SG, Kazarian JJ, Ojeda RP, Webb R, Wolstenholme R, Bleay S (2012) Chemical characterization of latent fingerprints by matrix-assisted laser desorption ionization, time-of-flight secondary ion mass spectrometry, mega electron volt secondary mass spectrometry, gas chromatography/mass spectrometry X-ray photoelectron spectroscopy. Anal Chem 84(20):8514–8523PubMedCrossRefGoogle Scholar
  12. 12.
    Bradshaw R, Rao W, Wolstenholme R, Clench MR, Bleay S, Francese S (2012) Separation of overlapping fingermarks by matrix assisted laser desorption ionisation mass spectrometry imaging. Forensic Sci Int 222(1–3):318–326PubMedCrossRefGoogle Scholar
  13. 13.
    Francese S, Bradshaw R, Ferguson LS, Wolstenholme R, Clench MR, Bleay S (2013) Beyond the ridge pattern: multi-informative analysis of latent fingermarks by MALDI mass spectrometry. Analyst 138(15):4215–4228PubMedCrossRefGoogle Scholar
  14. 14.
    De Alcaraz-Fossoul J, Mestres Patris C, Balaciart Muntaner A, Barrot Feixat C, Gené Badia M (2013) Determination of latent fingerprint degradation patterns—a real fieldwork study. Int J Legal Medicine 127(4):857–870CrossRefGoogle Scholar
  15. 15.
    Barros RM, Faria BF, Kuckelhaus SA (2013) Morphometry of latent palmprints as a function of time. Sci Justice 53(4):402–408PubMedCrossRefGoogle Scholar
  16. 16.
    De Alcaraz-Fossoul J, Roberts KA, Barrot-Feixat C, Hogrebe G, Gené Badia M (2016) Fingermark ridge drift. Forensic Sci Int 258:26–31PubMedCrossRefGoogle Scholar
  17. 17.
    De Alcaraz-Fossoul J, Mestres Patris C, Barrot Feixat C, Brandelli D, McGarr L, Stow K, Gené Badia M (2016) Latent fingermark aging patterns (Part I): minutiae count as one indicator of degradation. J Forensic Sci 61(2):322–333PubMedCrossRefGoogle Scholar
  18. 18.
    De Alcaraz-Fossoul J, Barrot Feixat C, Tasker J, McGarr L, Stow K, Carreras-Marin C, Gené Badia M (2016) Latent fingermark aging patterns (Part II): colour contrast between ridges and furrows as one indicator of degradation. J Forensic Sci 61(4):947–958PubMedCrossRefGoogle Scholar
  19. 19.
    De Alcaraz-Fossoul J, Barrot Feixat C, Tasker J, Carreras-Marin C, Zapico SC, Gené Badia M (2017) Latent fingermark aging patterns (Part III): discontinuity index as one indicator of degradation. J Forensic Sci 62(5):1180–1187PubMedCrossRefGoogle Scholar
  20. 20.
    Dorakumbura BN, Becker T, Lewis SW (2016) Nanomechanical mapping of latent fingermarks: a preliminary investigation into the changes in surface interactions and topography over time. Forensic Sci Int 267:16–24PubMedCrossRefGoogle Scholar
  21. 21.
    Wei Q, Zhang M, Ogorevc B, Zhang X (2016) Recent advances in the chemical imaging of human fingermarks (a review). Analyst 141(22):6172–6189PubMedCrossRefGoogle Scholar
  22. 22.
    De Alcaraz-Fossoul J, Mancenido M, Soignard E, Silverman N (2018) Application of 3D imaging technology to latent fingermark aging studies. J Forensic Sci ( https://doi.org/10.1111/1556-4029.13891; ahead of print)
  23. 23.
    Li B, Beveridge P, O’Hare WT, Islam M (2011) The estimation of the age of a blood stain using reflectance spectroscopy with a microspectrophotometer, spectral pre-processing and linear discriminant analysis. Forensic Sci Int 212(11):198–204PubMedGoogle Scholar
  24. 24.
    Li B, Beveridge P, O’Hare WT, Islam M (2013) The age estimation of blood stains up to 30 days old using visible wavelength hyperspectral image analysis and linear discriminant analysis. Sci Justice 53(3):270–277PubMedCrossRefGoogle Scholar
  25. 25.
    Dror IE, Charlton D, Péron AE (2006) Contextual information renders experts vulnerable to making erroneous identifications. Forensic Sci Int 156(1):74–78PubMedCrossRefGoogle Scholar
  26. 26.
    Charlton D, Fraser-Mackenzie PA, Dror IE (2010) Emotional experiences and motivating factors associated with fingerprint analysis. J Forensic Sci 55(2):385–393PubMedCrossRefGoogle Scholar
  27. 27.
    Fraser-Mackenzie PA, Dror IE, Wertheim K (2013) Cognitive and contextual influences in determination of latent fingerprint suitability for identification judgments. Sci Justice 53(2):144–153PubMedCrossRefGoogle Scholar
  28. 28.
    Kellman PJ, Mnookin JL, Erlikhman G, Garrigan P, Ghose T, Mettler E, Charlton D, Dror IE (2014) Forensic comparison and matching of fingerprints: using quantitative image measures for estimating error rates through understanding and predicting difficulty. PLoS ONE 9(5):e94617PubMedPubMedCentralCrossRefGoogle Scholar
  29. 29.
    Ulery BT, Hicklin RA, Buscaglia J, Roberts MA (2011) Accuracy and reliability of forensic latent fingerprint decisions. PNAS 108(19):7733–7738PubMedCrossRefGoogle Scholar
  30. 30.
    Mnookin J, Kellman PJ, Dror I, Erlikhman G, Garrigan P, Ghose T, Metler E, Charlton D (2016) Error rates for latent fingerprinting as a function of visual complexity and cognitive difficulty. Report. NIJ Award 2009-DN-BX-K225Google Scholar
  31. 31.
    Dror I (2013) The ambition to be scientific: human expert performance and objectivity. Sci Justice 53(2):81–82PubMedCrossRefGoogle Scholar
  32. 32.
    Kassin SM, Kukucka J, Lawson VZ, DeCarlo J (2014) Does video recording alter the behavior of police during interrogation? A mock crime-and-investigation study. Law Hum Behav 38(1):73–83PubMedCrossRefGoogle Scholar
  33. 33.
    Campbell R, Sefl T, Barnes HE, Ahrens CE, Wasco SM, Zaragoza-Diesfeld Y (1999) Community services for rape survivors: enhancing psychological well-being or increasing trauma? J Consult Clin Psychol 67(6):847–858PubMedCrossRefGoogle Scholar
  34. 34.
    Wertheim K (2003) Fingerprint age determination: is there any hope? J Forensic Ident 53(1):42–49Google Scholar
  35. 35.
    Champod C, Lennard C, Margot P, Stoilovic M (2004) Fingerprints and other ridge skin impressions, 1st ed., CRC PressGoogle Scholar
  36. 36.
    Hicklin RA, Buscaglia J, Roberts MA, Meagher SB, Burge MJ, Vera D, Pantzer LR, Calvin C (2011) Latent fingerprint quality: a survey of examiners. J Forensic Ident 61(4):385–418Google Scholar
  37. 37.
    Merkel R (2014) New solutions for an old challenge: chances and limitations of optical, non-invasive acquisition and digital processing techniques for the age estimation of latent fingerprints. Doctoral Thesis Universität MagdeburgGoogle Scholar
  38. 38.
    de Groot P (2015) Principles of interference microscopy for the measurement of surface topography. Adv Opt Photon 7:1–65CrossRefGoogle Scholar
  39. 39.
    Cadd S, Islam M, Manson P, Bleay S (2015) Fingerprint composition and aging: a literature review. Sci Justice 55(4):219–238PubMedPubMedCentralCrossRefGoogle Scholar
  40. 40.
    Matuszewski S, Szafałowicz M (2013) A simple computer-assisted quantification of contrast in a fingerprint. J Forensic Sci 58(5):1310–1313PubMedCrossRefGoogle Scholar
  41. 41.
    van Dam A, Aalders MC, Todorovski T, van Leeuwen TG, Lambrechts SA (2016) On the autofluorescence of aged fingermarks. Forensic Sci Int 258:19–25PubMedCrossRefGoogle Scholar
  42. 42.
    Rosa R, Giovanardi R, Bozza A, Veronesi P, Leonelli C (2017) Electrochemical impedance spectroscopy: a deeper and quantitative insight into the fingermarks physical modifications over time. Forensic Sci Int 273:144–152PubMedCrossRefGoogle Scholar
  43. 43.
    Williams DK, Brown CJ, Bruker J (2011) Characterization of children’s latent fingerprint residues by infrared microspectroscopy: forensic implications. Forensic Sci Int 206(1–3):161–165PubMedCrossRefGoogle Scholar
  44. 44.
    Girod A, Weyermann C (2014) Lipid composition of fingermark residue and donor classification using GC/MS. Forensic Sci Int 238:68–82PubMedCrossRefGoogle Scholar
  45. 45.
    Croxton RS, Baron MG, Butler D, Kent T, Sears VG (2006) Development of a GC-MS method for the simultaneous analysis of latent fingerprint components. J Forensic Sci 51(6):1329–1333PubMedCrossRefGoogle Scholar
  46. 46.
    Wolstenholme R, Francese S, Bradshaw R (2010) Study of lipid distribution and degradation in latent fingerprints by spectroscopic imaging techniques. Sci Justice 50(1):37–38CrossRefGoogle Scholar
  47. 47.
    Ferguson L, Bradshaw R, Wolstenholme R, Clench M, Francese S (2011) Two-step matrix application for the enhancement and imaging of latent fingermarks. Anal Chem 83(14):5585–5591PubMedCrossRefGoogle Scholar
  48. 48.
    Ferguson LS, Wulfert F, Wolstenholme R, Fonville JM, Clench MR, Carolan VA, Francese S (2012) Direct detection of peptides and small proteins in fingermarks and determination of sex by MALDI mass spectrometry profiling. Analyst 137(20):4686–4692PubMedCrossRefGoogle Scholar
  49. 49.
    Bradshaw R, Bleay S, Wolstenholme R, Clench MR, Francese S (2013) Towards the integration of matrix assisted laser desorption ionisation mass spectrometry imaging into the current fingermark examination workflow. Forensic Sci Int 232(1–3):111–124PubMedCrossRefGoogle Scholar
  50. 50.
    Ferguson LS, Creasey S, Wolstenholme R, Clench MR, Francese S (2013) Efficiency of the dry-wet method for the MALDI-MSI analysis of latent fingermarks. J Mass Spectrom 48(6):677–684Google Scholar
  51. 51.
    Reed H, Stanton A, Wheat J, Kelley J, Davis L, Rao W, Smith A, Owen D, Francese S (2016) The Reed-Stanton press rig for the generation of reproducible fingermarks: towards a standardised methodology for fingermark research. Sci Justice 56(1):9–17PubMedCrossRefGoogle Scholar
  52. 52.
    Liu F, Liang J, Shen L, Yang M, Zhang D, Lai Z (2017) Case study of 3D fingerprints applications. PLoS ONE 12(4):e0175261PubMedPubMedCentralCrossRefGoogle Scholar
  53. 53.
    Stoehr B, McClure S, Höflich A, Al Kobaisi M, Hall C, Murphy PJ, Evans D (2016) Unusual nature of fingerprints and the implications for easy-to-clean coatings. Langmuir 32(2):619–625PubMedCrossRefGoogle Scholar
  54. 54.
    Finnis J, Lewis J, Davidson A (2013) Comparison of methods for visualizing blood on dark surfaces. Sci Justice 53(2):178–186PubMedCrossRefGoogle Scholar
  55. 55.
    Home Office CAST (2013) Fingerprint Sourcebook, Chapter 3, 3.1 Acid Dyes, 1st ed., Home OfficeGoogle Scholar
  56. 56.
    Li B, Beveridge P, O’Hare WT, Islam M (2014) The application of visible wavelength reflectance hyperspectral imaging for the detection and identification of blood stains. Sci Justice 54(6):432–438PubMedCrossRefGoogle Scholar
  57. 57.
    Passi N, Kumar Garg R, Yadav M, Sarup Singh R, Kharoshah MA (2012) Effect of luminol and bleaching agent on the serological and DNA analysis from bloodstain. Egypt J Forensic Sci 2(2):54–61CrossRefGoogle Scholar
  58. 58.
    Anderson S, Howard B, Hobbs GR, Bishop CP (2005) A method for determining the age of a bloodstain. Forensic Sci Int 148(1):37–45PubMedCrossRefGoogle Scholar
  59. 59.
    Bremmer RH, Nadort A, van Leeuwen TG, van Gemert MJC, Aalders MCG (2011) Age estimation of blood stains by hemoglobin derivative determination using reflectance spectroscopy. Forensic Sci Int 206(1–3):166–171PubMedCrossRefGoogle Scholar
  60. 60.
    De Wael K, Lepot L, Gason F, Gilbert B (2008) In search of blood—detection of minute particles using spectroscopic methods. Forensic Sci Int 180(1):37–42PubMedCrossRefGoogle Scholar
  61. 61.
    Chun-Yen Lin A, Hsieh H, Tsai L, Linacre A, Lee JC (2007) Forensic applications of infrared imaging for the detection and recording of latent evidence. J Forensic Sci 52(5):1148–1150CrossRefGoogle Scholar
  62. 62.
    McLaughlin G, Sikirzhytski V, Lednev IK (2013) Circumventing substrate interference in the Raman spectroscopic identification of blood stains. Forensic Sci Int 231(1–3):157–166PubMedCrossRefGoogle Scholar
  63. 63.
    Stoilovic M (1991) Detection of semen and blood stains using polilight as a light source. Forensic Sci Int 51(2):289–296PubMedCrossRefGoogle Scholar
  64. 64.
    Strasser S, Zink A, Kada G, Hinterdorfer P, Peschel O, Heckl WM, Nerlich AG, Thalhammer S (2007) Age determination of blood spots in forensic medicine by force spectroscopy. Forensic Sci Int 170(1):8–14PubMedCrossRefGoogle Scholar
  65. 65.
    Turrina S, Filippini G, Atzei R, Zaglia E, De Leo D (2008) Validation studies of rapid stain identification-blood (RSID-blood) kit in forensic caseworks. Forensic Sci Int Genet Suppl Ser 1(1):74–75CrossRefGoogle Scholar
  66. 66.
    Wawryk J, Odell M (2005) Fluorescent identification of biological and other stains on skin by the use of alternative light sources. J Clin Forensic Med 12(6):296–301PubMedCrossRefGoogle Scholar
  67. 67.
    Gardner T, Anderson T (2009) Criminal evidence: principles and cases, 7th edn. Cengage Learning, Belmont, CAGoogle Scholar
  68. 68.
    Adebsi S (2009) Fingerprint studies—the recent challenges and advancements: a literary view. Internet J Biol Anthropol 2(2):3Google Scholar
  69. 69.
    Midkiff C (1993) Lifetime of a latent print how long can you tell? J Forensic Ident 43(4):386–396Google Scholar
  70. 70.
    Bremmer RH, de Bruin KG, van Leeuwen TG, van Gemert MJC, Aalders MCG (2012) Forensic quest for age determination of bloodstains. Forensic Sci Int 216(1–3):1–11PubMedCrossRefGoogle Scholar
  71. 71.
    Janchaysang S, Sumriddetchkajorn S, Buranasiri P (2012) Tunable filter-based multispectral imaging for detection of blood stains on construction material substrates part 1: developing blood stain discrimination criteria. Appl Opt 51(29):6984–6996PubMedCrossRefGoogle Scholar
  72. 72.
    Janchaysang S, Sumriddetchkajorn S, Buranasiri P (2013) Tunable filter-based multispectral imaging for detection of blood stains on construction material substrates part 2: realization of rapid blood stain detection. Appl Opt 52(20):4898–4910PubMedCrossRefGoogle Scholar
  73. 73.
    Edelman GJ, Gaston E, van Leeuwen TG, Cullen PJ, Aalders MCG (2012) Hyperspectral imaging for non-contact analysis of forensic traces. Forensic Sci Int 223(1–3):28–39PubMedCrossRefGoogle Scholar
  74. 74.
    Cadd S, Li B, Beveridge P, O’Hare WT, Campbell A, Islam M (2016) Non-contact detection and identification of blood stained fingerprints using visible wavelength reflectance hyperspectral imaging: part 1. Sci Justice 56(3):181–190PubMedCrossRefGoogle Scholar
  75. 75.
    Cadd S, Li B, Beveridge P, O’Hare WT, Islam M (2016) The non-contact detection and identification of blood stained fingerprints using visible wavelength hyperspectral imaging: part II effectiveness on a range of substrates. Sci Justice 56(3):191–200PubMedCrossRefGoogle Scholar
  76. 76.
    Cadd S, Li B, Beveridge P, O’Hare WT, Campbell A, Islam M (2016) A comparison of visible wavelength reflectance hyperspectral imaging and Acid Black 1 for the detection and identification of blood stained fingerprints. Sci Justice 56(4):247–255PubMedCrossRefGoogle Scholar
  77. 77.
    Weyermann C, Ribaux O (2012) Situating forensic traces in time. Sci Justice 52(2):68–75PubMedCrossRefGoogle Scholar
  78. 78.
    Neumann C, Stern H (2016) Forensic examination of fingerprints: past, present, and future. Chance 29(1):9–16CrossRefGoogle Scholar
  79. 79.
    Cadd S, Li B, Beveridge P, O’Hare WT, Islam M (2018) Age determination of blood-stained fingerprints using visible wavelength reflectance hyperspectral imaging. J Imag 4(12):141CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Henry C. Lee College of Criminal Justice and Forensic SciencesUniversity of New HavenWest HavenUSA
  2. 2.School of Science, Engineering and DesignTeesside UniversityMiddlesbroughUK

Personalised recommendations