We present a machine vision system for automatic identification of the class of firearms by extracting and analyzing two
significant properties from spent cartridge cases, namely the Firing Pin Impression (FPI) and the Firing Pin Aperture
Outline (FPAO). Within the framework of the proposed machine vision system, a white light interferometer is employed
to image the head of the spent cartridge cases. As a first step of the algorithmic procedure, the Primer Surface Area
(PSA) is detected using a circular Hough transform. Once the PSA is detected, a customized statistical region-based
parametric active contour model is initialized around the center of the PSA and evolved to segment the FPI.
Subsequently, the scaled version of the segmented FPI is used to initialize a customized Mumford-Shah based level set
model in order to segment the FPAO. Once the shapes of FPI and FPAO are extracted, a shape-based level set method is
used in order to compare these extracted shapes to an annotated dataset of FPIs and FPAOs from varied firearm types. A
total of 74 cartridge case images non-uniformly distributed over five different firearms are processed using the
aforementioned scheme and the promising nature of the results (95% classification accuracy) demonstrate the efficacy of
the proposed approach.
For the first time, transmission digital holography microscopy is applied to observe coal palynofacies, which are organic
fossil microcomponents contained in the coal grains. The recorded holograms were produced by using microscope lenses
with 20x and 40x of lateral magnification respectively, and He-Ne laser of wavelength 594.5 nm. The results show that
reflection digital holography microscopy is required for observing relative opaque particles, because the phase recovery
is strong diminished by light transmission in those cases. On the other hand, the phase distribution is related to the relief
of the particles and the variations of their refraction index. Therefore, a priori information should be necessary to
properly relate the phase information to physical features of the particles. Numerical unwrapping procedures are also
crucial. Procedures with special requirements can be needed for analysing fast varying phase distributions. However,
digital holography microscopy becomes a high performance tool for 3D modelling of fossil particles if the above
requirements are enough fulfilled.
Techniques of digital holography are improved in order to obtain high-resolution, high-fidelity images of quantitative phase-contrast microscopy. In particular, the angular spectrum method of calculating the holographic optical field is seen to have several advantages over the more commonly used Fresnel transformation or Huygens convolution method. Spurious noise and interference components can be tightly controlled through the analysis and filtering of the angular spectrum. The reconstruction distance does not have a lower limit and the off-axis angle between the object and reference can be lower than the Fresnel requirement and still be able to cleanly separate out the zero-order background. Holographic phase images are largely immune from the coherent noise common in amplitude images. Together with the use of a miniature pulsed laser, the resulting images have 0.5μm diffraction-limited lateral resolution and the phase profile is accurate to about 30 nm of optical path length. SKOV-3 (ovarian cancer cells) and HUVEC (human umbilical vein endothelial cells) are imaged that display intra-cellular and intra-nuclear organelles with clarity and quantitative accuracy. The technique clearly exceeds currently available methods in phase-contrast optical microscopy in the level of resolution and detail, and provides a new modality for imaging morphology of cellular and intracellular structures that is not currently available.