Breaking NEWz you can UzE...
compiled by Jon Stimac
Fingerprint Expert Takes Stand in Padilla Trial –
LOS ANGELES TIMES, CA May 18, 2007
...suspect's fingerprints match at least seven of 45 latent prints
found on an alleged application for Al Qaeda training...
Thumbprint Sheds Light on County Cold Cases –
VALLEJO TIMES-HERALD, CA -
2007 ...one thumbprint has turned out to be
the solution to a pair of 10-year-old Solano County cold cases...
Cold Case is Coldest Ever for Crime Lab
DAYTON DAILY NEWS. OH
- May 16, 2007
...fingerprint identification help sheriff's detectives make an arrest
in the 36-year-old homicide investigation...
BOSTON GLOBE, MA
2007 ...in the middle of a troubling crime wave, Boston
Police Department's once embattled fingerprint lab is now a well-oiled
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We review a recent article
published in the Journal of Forensic Sciences related to latent print
Infrared Spectroscopic Imaging for Noninvasive Detection of Latent
by Nicole Crane, Edward Bartick, Rebecca Schwartz Perlman, and Scott Huffman
ABSTRACT: The capability of Fourier transform infrared (FTIR)
spectroscopic imaging to provide detailed images of unprocessed latent
fingerprints while also preserving important trace evidence is demonstrated.
Unprocessed fingerprints were developed on various porous and nonporous
substrates. Data-processing methods used to extract the latent fingerprint
ridge pattern from the background material included basic infrared
spectroscopic band intensities, addition and subtraction of band intensity
measurements, principal components analysis (PCA) and calculation of second
derivative band intensities, as well as combinations of these various
techniques. Additionally, trace evidence within the fingerprints was
recovered and identified.
While many techniques are established for a particular forensic evaluation,
specific analyses require re-examination and further research for two
primary reasons. First, there is the need to develop techniques to reduce
the time expended in performing an analysis, and, second, improvements in
analytical methodologies are required for providing more reliable,
unambiguous results. Developing new analytical approaches and conducting
validation studies assure that the most reliable forensic evidence will be
entered into the justice system.
In 1999, the U.S. Department of Justice published a document entitled
"Forensic Sciences: Review of Status and Needs" (1). One of the sections in
this publication was dedicated to "Methods Research, Development, Testing
and Evaluation." The current status and needs were listed for nine areas of
forensic science, including latent fingerprint examinations. According to
the document, latent fingerprints require "improved recovery and
visualization methods and detection of associative evidence in prints."
Latent fingerprints present a considerable challenge in forensics, as
invasive methods are often required for developing a print. Processing
techniques for fingerprints include chemicals, powders, and/or various light
sources (2–6), which may damage or destroy chemical associative trace
evidence within the fingerprint. Thus, a noninvasive procedure that captures
a digital image of the fingerprint, along with the chemical information
within that fingerprint, adds significantly to the tools available to the
Recently, the application of visible absorption and luminescence
spectroscopic imaging studies on latent fingerprint detection has produced
promising results (7–10). With visible imaging, the detection of untreated
latent prints on substrates such as acetate sheets and a white plastic bag
was possible (9). The authors indicated that ridge detail was detected on
untreated yellow paper. However, sufficient detail was not observable to
discern the ridge characteristics for identification. Visible imaging proved
more successful on treated substrates such as newspaper, money, glass, a
drug bag, and a plastic Ziplock® (S.C. Johnson Racine, WI) bag. In these
instances, the detection is not exclusively of the fingerprint but rather
the chemicals used to treat the latent prints. Associative trace evidence
contained within the print may be compromised because of the chemical
treatment. In addition, the detection of the latent prints is based on broad
visible absorptions that are not chemical component specific.
Unlike visible spectroscopy, mid-infrared (IR) spectroscopy is based on
molecular absorptions that are characteristic of specific molecular
structure resulting from the chemical composition of the material being
studied. Bartick et al. (11) and Williams et al. (12) used single detector
Fourier transform infrared (FTIR) microspectroscopy to characterize the
chemical composition of the various residues contained in adult and child
fingerprints. The chemistry of these residues varies among individuals and
contains both eccrine deposits from the fingers alone and sebaceous deposits
resulting from the depositor having previously touched various body parts,
such as the face or neck. Both classes of deposits consist of fatty acid
esters, protein from skin particles, and carboxylic acid salts, while
sebaceous material consists primarily of esters. As a person reaches
puberty, fingerprints often contain a higher concentration of sebaceous
matter. A representative IR spectrum, shown in Fig. 1 with associated band
assignments listed in Table 1 (13), illustrates the ability to discern
critical chemical components.
1—Infrared band assignments for spectrum (Fig.
1) of fingerprint residue (13).
||Asymmetric O–C–C stretch, ester
||Asymmetric C–C–O stretch, ester (C bonded to the O
included in the carbonyl)
||N–H bend combined with C–N stretch, protein amide II
||C=O stretch, protein amide I feature
||C=O stretch, saturated ester
||Methylene C–H stretch
||Methyl C–H stretch
spectrum of fingerprint residue on an aluminum slide.
Single detector IR spectroscopy is a common technique for the identification
of materials. IR is very useful in forensic applications, such as for trace
evidence and for drug analysis, by discerning both the organic and inorganic
components of the samples (14,15). IR spectroscopy may be implemented in an
imaging mode for a wide range of applications that include, for example,
pharmaceutical tablet examinations and histopathological tissue diagnostics
(16–30). IR imaging not only provides a spatial distribution of the
component materials, but an identification of individual constituents.
The application of FTIR for imaging of latent fingerprints was first
demonstrated by Bartick et al. (11) using spectral bands indicative of the
chemical components of the deposited material. The images were from prints
deposited on aluminum-coated glass microscope slides for representing a
reflective substrate. The detection of an explosive material, RDX, was
viewed and spectrally identified in a latent fingerprint composite spectral
image deposited on an aluminum-coated slide (31). More recently, in a study
by Tahtouh et al., (32) FTIR imaging performed well for the detection of
ethyl cyanoacrylate fumed latent prints on polymer banknotes, as well as
treated and untreated latent prints on glass. All detection and contrast of
the treated latent prints were based on the carbonyl stretching mode of the
ethyl cyanoacrylate at 1743 cm1. The contrast provided by FTIR imaging is
clearly superior to that of visible imaging. Our present study demonstrates
the ability of IR spectroscopic imaging to reveal latent print details on
challenging substrates without preprocessing or pretreating the latent
prints. However, in some cases, the print was slightly visible by eye. In
either case, processing with IR spectral imaging techniques rendered all
prints clearly visible.
Materials and Methods:
Fingerprints were deposited onto substrates after rubbing one's forehead.
All substrates were mounted onto MirrIR slides (Kevley Technologies,
Chesterland, OH) using clear cellophane tape on the edges of the substrates
to secure them to the slides. Substrates included nonporous (trash bags, a
soda can, tape) and porous (copier paper, cigarette butt paper, U.S. dollar
bill, postcard) materials. An image of the fingerprints on the various
substrates was first acquired with a PowerLook III scanner (Techville Inc.,
Dallas, TX), 1200 × 2400 dpi (Umax, http://www.umax.com). It is important to
note that the location of the fingerprints was known before collecting IR
Both visible and IR reflectance images were collected using a Spectrum
Spotlight 300 FTIR Microscope System, with a 100 μm × 100 μm microscope
aperture (Perkin Elmer, Shelton, CT). All visible reflectance images of the
samples were acquired before the IR image. IR backgrounds for the images
were collected in regions of the substrate without fingerprint residue and
used the same 4000–700 cm1 range as the corresponding IR images. The
background scan parameters included 120 scans/pixel at 16 cm1 spectral
resolution. The regions for the IR images were selected from within the
visible reflectance image, as indicated by black and white boxes
superimposed on the figures that follow, with sizes varying from 6.48 mm ×
7.15 mm (W × H) to 23.7 mm × 12.8 mm. All IR images were collected using the
reflectance and image mode with a pixel size of 25 μm. IR image parameters
included 4 scans/pixel at 16 cm1 spectral resolution. Fingerprint samples
were stored for up to 3 months; no spectral degradation of the fingerprints
was observed with varying lengths of storage time.
Once acquired, all spotlight IR images were imported into ENVI® software (RSI
Inc., Boulder, CO) using an "in-house written" program (available upon
request) that converted the Perkin Elmer data format into a data format
transferable to ENVI®. IR images were analyzed with varying techniques,
including band intensity images, addition and subtraction of band intensity
images, principal components analysis (PCA, specifically forward PC rotation
with new statistics), and second derivative band intensity images, as well
as appropriate combinations of these techniques. Both PCA and second
derivative calculations for IR image analysis have been discussed in detail
elsewhere (33). All data analysis performed in ENVI® used programs provided
within the software, except the program for calculating second derivative
For the band intensity images and second derivative band intensity images,
ester bands were commonly used to obtain images of the fingerprint residue.
Most images were obtained using the 1016 cm1 asymmetric O–C–C stretch ester
vibrational mode. Although the most intense 1744 cm1 carbonyl stretching
mode of the ester may also have been used, the weaker 1016 cm1 mode provided
images with superior clarity. The reason for the enhanced results using the
1016 cm1 band is not clear to the authors and is under investigation. For
data not shown here, comparable images were obtained using additional
vibration bands (1552, 1664, and 1744 cm1).
In addition, a reflectance spectrum of a blue, cylindrical fiber on the
postcard was acquired. The fiber was removed from the postcard and mounted
onto a MirrIR slide via an adhesive fiber holder. The spectrum was collected
over the range of 4000–700 cm1 at 1 cm1 intervals and a total of 32 scans.
The fiber spectrum was automatically baselined and matched to its fiber
components in the Perkin Elmer spectrum® software (Wellesley, MA) using the
FBI fiber library (Version 4.0).
Results and Discussion:
The thickness of the substrates required that images be determined in
reflectance mode. For this experiment, the soda can sample was deemed to be
the simplest substrate because its aluminum sheet with paint would promote
the greatest reflectance. An untreated fingerprint deposited onto a Dr.
Pepper's® (Cadbury Schweppes Americas Beverages, Plano, TX) soda can is
shown in Fig. 2A. While the fingerprint on the soda can is visible with the
visible scanning technique, areas of paint on the can conceal portions of
the fingerprint. By plotting the vibrational band intensity at 1016 cm1
(Fig. 2B), the fingerprint contrast is greatly enhanced. For this example,
the use of additional mathematical algorithms is not necessary, as an image
based on band intensity is all that is required.
2—Cut and flattened Dr. Pepper's soda can with fingerprint deposit.
(A) Soda can imaged by a document scanner. (B) Infrared image of the
outlined area obtained by plotting the band intensity at 1016 cm1.
Figure 3A shows an untreated fingerprint deposited onto a black trash bag.
This substrate is more challenging as the substrate is less reflective and
is not flat. In spite of these challenges, Fig. 3B displays a virtually
unobstructed fingerprint image based on the 1016 cm1 band intensity. Again,
complicated algorithms were not required for fingerprint visualization.
Areas of the image where wrinkles were present appear smudged on the IR
image, but adequate fingerprint detail is retained for these areas.
3—Black, plastic garbage bag with a fingerprint, taped flat. (A)
Trash bag imaged by a document scanner. (B) Infrared image of the
outlined area obtained by plotting the band intensity at 1016 cm1.
Duct tape is a more heterogeneous substrate compared with a soda can or
trash bag. As duct tape contains a plastic and woven backing, as well as
adhesive, and as it is not completely flat, variations are noted in the
image profile. The brand of tape shown in Fig. 4A does not have the typical
silver color of duct tape but rather a nonreflective, semitransparent yellow
color. Simple plotting of band intensity for imaging is not successful for
this particular substrate; thus, further mathematical processing is
required. By subtracting the band intensity image of the tape at 696 cm1
from the band intensity image of the fingerprint residue at 1016 cm1, a
fingerprint is visible on the tape without the use of chemicals, as can be
seen in Fig. 4B. Unlike the previous examples presented here, FTIR imaging
was able to develop a print spectroscopically that was not otherwise
deposited onto a duct tape-like tape. (A) Tape imaged by a document
scanner. (B) Infrared image of the outlined area obtained by band math,
the subtraction of the band intensity at 696 cm1
from the band intensity at 1016 cm1.
Paper, due to its porosity, represents a challenging substrate for the
spectroscopic development of fingerprints. For example, fingerprint residue
is barely visible on the unprocessed white copier paper shown in Fig. 5A.
Until now, the examples discussed for obtaining fingerprint images have been
from nonporous materials. Porous materials like paper have low reflectivity,
are absorbent, and heterogeneous (nonuniform distribution and orientation of
paper fibers). The application of band intensity images was not sufficient
for rendering this fingerprint visible. For this example, two methods were
compared: PCA and second derivatization. PCA calculations are performed to
extract component spectra and have been frequently used for spectral imaging
enhancement (8,10,34). The PCA-derived image is shown in Fig. 5B. Although a
partial fingerprint is revealed, a portion remains obscured by the paper
fibers. Figure 5C shows a successful depiction of the entire fingerprint on
the copier paper. The fingerprint in Fig. 5C was obtained by performing a
second derivative calculation on all of the spectra in the image and then by
plotting the band intensity at 1016 cm1. The second derivative calculations
provided superior results compared with PCA for two reasons. First, because
PCA calculates the principal components of the image based on spectral
variation, the fingerprint becomes less visible in the lower right areas of
Fig. 5A and B. Second, by minimizing background features in the spectrum,
such as the broad spectral interference from paper, the second derivative of
the spectrum allows the narrow spectral features to become prominent.
deposited onto white copier paper. (A) Copier paper with fingerprint as
imaged by a document scanner. (B) Infrared image outlined area obtained
using principal components analysis. (C) Infrared image outlined area from
second derivative spectral band intensity at 1016 cm1.
Cigarette butt paper differs from that of copier paper because it is more
porous. Figure 6A shows the cigarette butt paper removed from the filter and
flattened onto a microscope slide. Note that the fingerprint is not at all
visible. Merely plotting the band intensity at 1016 cm1 was inadequate for
fingerprint development; however, once the second derivative spectra were
calculated and the band intensity was again plotted for the 1016 cm1
feature, the fingerprint was clearly observed (Fig. 6B) with no interference
from the paper substrate.
butt paper removed from cigarette filter, flattened, and deposited with
fingerprint. (A) Cigarette butt paper as imaged by a document scanner. (B)
Infrared image of outlined area by using the second derivative band
intensity at 1016 cm1.
Paper money may present difficulties as the substrate contains not only
paper, but various inks, foils, and fibers. A scanned image of a portion of
a U.S. one dollar bill is shown in Fig. 7A. A fingerprint is not visible on
the scanned image of the bill; however, calculation of second derivative
spectra and a plot of the 1016 cm1 band intensity reveal a fingerprint (Fig.
7B). Figures 7C and D show components isolated within the bill. On the U.S.
dollar bill, the number "3" and the border design are black in color. By
simple visual inspection, it is not clear whether the number "3" and the
border design are derived from the same ink. However, from the addition and
subtraction of various band intensity images, we note that the number "3"
and the border design are representative of two different inks. This type of
spectral differentiation would be useful to characterize counterfeit money.
Thus, evidence is more valuable because there is not only the possibility of
counterfeit identification but also a direct link and possible
identification of the criminal if a fingerprint is present.
dollar bill with a latent print. (A) Scanned image of a U.S. one dollar
bill. (B) Infrared image of the outlined area of a dollar bill, revealed
by using the second derivative band intensity at 1016 cm1.
Isolation of the number "3" (C) and border design (D) on the bill obtained
by second derivative band math.
The last example of IR imaging for non-invasive fingerprint detection
involves a postcard (Fig. 8A). Upon visual inspection, the fingerprint
appears somewhat smeared and little detail is retained. Fortunately, the
postcard has the advantage of a semiglossy coating, which increases the
overall reflectance of the substrate. However, the substrate is a semiporous
cardboard-like material with four different inks in various layers. The use
of PCA enabled us to separate the postcard into its various components,
revealing at least three of the inks and, most importantly, the fingerprint
with latent print. (A) Scanned image of postcard. Note the fiber (blue in
color) on the postcard, denoted by the circle. (B) Infrared image of
outlined area, obtained by principal components analysis.
Within the small circle in Fig. 8A appears a blue fiber. This is an instance
when the initial evidence contains additional associative evidence. By
developing the fingerprint noninvasively, the fiber can be spectroscopically
analyzed. By using another print development technique, the chemicals used
may have obscured the spectral "fingerprint" of the fiber itself. In this
case, the fiber was removed from the postcard and analyzed using single
detector FTIR spectroscopy. The fiber was rolled and mounted onto a
reflective glass slide. The blue, cylindrical fiber has a diameter of
approximately 25 μm (Fig. 9A). Several spectra were collected along various
locations on the fiber shaft. After comparing the fiber spectrum with the
FBI fiber database, the fiber was identified as likely being rayon (Fig.
9B). Additional peaks in the spectrum that are not evident in the spectrum
of rayon likely result from fingerprint residue, thus suggesting that the
fiber should have been cleaned. The cylindrical morphology of the fiber
supports the identification of the fiber as rayon over cotton with a
cellulose component material.
Image of fiber removed from postcard, as seen by a color charge coupled
device camera on an infrared microscope. (B) Spectral comparison of blue
fiber with Federal Bureau of Investigation fiber database rayon fiber.
Other substrates examined, but not presented in this manuscript, were glass,
double-sided clear cellophane tape, electrical tape, an opaque white tape
with orange printing, a white, opaque trash bag, a white, translucent trash
bag, a plastic knife handle, green-colored copier paper, a magazine page,
cigarette shaft paper, cardboard, a Kimwipe® (Kimberly-Clark Corp., Neenah,
WI) tissue, and, overlapping prints on a manila envelope. Latent prints were
detected on all of the above substrates, except for cardboard and the
Kimwipe® tissue, perhaps because of the porosity and fibrous nature of these
two materials. Individual overlapping prints on the manila envelope were
resolved, using spectral differences in the second derivative spectra of the
In this study, FTIR imaging was used for the noninvasive detection of latent
fingerprints and was accomplished in such a manner as to preserve trace
evidence associated with the prints. This enables the analyst to make a
direct connection between the fingerprint and the trace evidence without
altering the state of the evidence. Untreated latent prints on various
nonporous and porous substrates were imaged. Various analysis techniques,
including band intensity, addition and subtraction of band intensity, PCA,
and second derivative band intensity, were utilized to improve the print
images on the substrates. In addition to detecting prints, additional
forensic information was obtained using FTIR. For example, a fiber was found
and identified within a fingerprint on a postcard. In addition to the latent
print detected on paper money, different chemical components characterizing
the inks on the bill were also indicated.
In general, this method works well when one knows where to look for latent
fingerprints. With work toward validating the methods demonstrated here,
case work applications appear viable. Additionally, future studies are being
considered for further instrumental development where IR imaging could be
used as a field technique for the noninvasive detection of both latent
fingerprints and trace evidence.
The authors would like to thank Rohit Bhargava for his programing
assistance. We would also like to thank Ira W. Levin for his helpful
discussions on this particular study. The authors would also like to
acknowledge partial support from the Intramural Research Program of the
National Institute of Diabetes and Digestive and Kidney Diseases.
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