Surface analysis and fingerprint recognition from multi-light imaging collections

Multi-light imaging captures a scene from a fixed viewpoint through multiple photographs, each of which are illuminated from a different direction. Every image reveals information about the surface, with the intensity reflected from each point being measured for all lighting directions. The images captured are known as multi-light image collections (MLICs), for which a variety of techniques have been developed over recent decades to acquire information from the images. These techniques include shape from shading, photometric stereo and reflectance transformation imaging (RTI). Pixel coordinates from one image in a MLIC will correspond to exactly the same position on the surface across all images in the MLIC since the camera does not move. We assess the relevant literature to the methods presented in this thesis in chapter 1 and describe different types of reflections and surface types, as well as explaining the multi-light imaging process. In chapter 2 we present a novel automated RTI method which requires no calibration equipment (i.e. shiny reference spheres or 3D printed structures as other methods require) and automatically computes the lighting direction and compensates for non-uniform illumination. Then in chapter 3 we describe our novel MLIC method termed Remote Extraction of Latent Fingerprints (RELF) which segments each multi-light imaging photograph into superpixels (small groups of pixels) and uses a neural network classifier to determine whether or not the superpixel contains fingerprint. The RELF algorithm then mosaics these superpixels which are classified as fingerprint together in order to obtain a complete latent print image, entirely contactlessly. In chapter 4 we detail our work with the Metropolitan Police Service (MPS) UK, who described to us with their needs and requirements which helped us to create a prototype RELF imaging device which is now being tested by MPS officers who are validating the quality of the latent prints extracted using our technique. In chapter 5 we then further developed our multi-light imaging latent fingerprint technique to extract latent prints from curved surfaces and automatically correct for surface curvature distortions. We have a patent pending for this method

Large Area Crop Inventory Experiment (LACIE). Second-generation sampling strategy evaluation report

The author has identified the following significant results. The stratification procedure in the new sampling strategy for LACIE included: (1) correlation test results indicating that an agrophysical stratum may be homogeneous with respect to agricultural density, but not with respect to wheat density; and (2) agrophysical unit homogeneity test results indicating that with respect to agricultural density many agrophysical units are not homogeneous, but removal of one or more refined strata from any such current agrophysical unit can make the strata homogeneous. The apportioning procedure results indicated that the current procedure is not performing well and that the apportioned estimates of refined strata wheat area are often unreliable

Remote Extraction of Latent Fingerprints (RELF)

This is the author accepted manuscript. The final version is available from IEEE via the DOI in this recordLatent fingerprints are the kind left on objects after direct contact with a person’s finger, often unwittingly at crime scenes. Most current techniques for extracting these types of fingerprint are invasive and involve contaminating the fingerprint with chemicals which often renders the fingerprint unusable for further forensic testing. We propose a novel and robust method for extracting latent fingerprints from surfaces without the addition of contaminants or chemicals to the evidence. We show our technique works on notoriously difficult to image surfaces, using off-the-shelf cameras and statistical analysis. In particular, we extract images of latent fingerprints from surfaces which are transparent, curved and specular such as glass lightbulbs and jars, which are challenging due to the curvature of the surface. Our method produces results comparable to more invasive methods and leaves the fingerprint sample unaffected for further forensic analysis. Our technique uses machine learning to identify partial fingerprints between successive images and mosaics them

Ecclesial Practices

In this chapter, we first provide an overview of the place of practice in some of the most prominent recent epistemologists of religion; second, we give an account of an ordinary practice (engineering) to flesh out a general conception of the importance of practice in training cognizers for skilled perception; third, and last, we connect the results of this inquiry with renewed theological and philosophical interest in the ‘spiritual senses’ tradition. The upshot of these reflections is the conclusion that an adequate account of social practices already anticipates the possibility that ecclesial practice might contribute to an epistemic transformation capable of realizing new (spiritual) perceptional capacities by the transformed

Phenotypic divergence along lines of genetic variance

Natural populations inhabiting the same environment often independently evolve the same phenotype. Is this replicated evolution a result of genetic constraints imposed by patterns of genetic covariation? We looked for associations between directions of morphological divergence and the orientation of the genetic variance-covariance matrix (G) by using an experimental system of morphological evolution in two allopatric nonsister species of rainbow fish. Replicate populations of both Melanotaenia eachamensis and Melanotaenia duboulayi have independently adapted to lake versus stream hydrodynamic environments. The major axis of divergence (z) among all eight study populations was closely associated with the direction of greatest genetic variance (g(max)), suggesting directional genetic constraint on evolution. However, the direction of hydrodynamic adaptation was strongly associated with vectors of G describing relatively small proportions of the total genetic variance, and was only weakly associated with g(max). In contrast, divergence between replicate populations within each habitat was approximately proportional to the level of genetic variance, a result consistent with theoretical predictions for neutral phenotypic divergence. Divergence between the two species was also primarily along major eigenvectors of G. Our results therefore suggest that hydrodynamic adaptation in rainbow fish was not directionally constrained by the dominant eigenvector of G. Without partitioning divergence as a consequence of the adaptation of interest (here, hydrodynamic adaptation) from divergence due to other processes, empirical studies are likely to overestimate the potential for the major eigenvectors of G to directionally constrain adaptive evolution

Large Area Crop Inventory Experiment (LACIE). Intensive test site assessment report

There are no author-identified significant results in this report

2017 McDonald diagnostic criteria: A review of the evidence

The diagnosis of Multiple Sclerosis (MS) has continuously evolved, allowing for an earlier and more accurate diagnosis of MS over time. The McDonald Criteria for diagnosis of MS were originally proposed in 2001, with previous revisions in both 2005 and 2010. The International Panel on Diagnosis in MS have recently reviewed the 2010 McDonald Criteria, and made recommendations for the revised 2017 McDonald Criteria. Any revisions made relied entirely on the available evidence, and not expert opinion. In this review, we provide an overview of the recent 2017 revisions to the McDonald Criteria, focusing in particular on the motivating evidence behind the recommendations made. We also review the existing research around misdiagnosis in MS, as well as areas considered to be high priorities of research, currently lacking in sufficient evidence, which may influence future diagnostic criteria in years to come. Finally, we illustrate some clinical examples, to demonstrate the impact of new diagnostic criteria on time to MS diagnosis in a real-world setting