Polarization- and Specular-Reflection-Based, Non-contact Latent Fingerprint Imaging and Lifting

In forensic science the finger marks left unintentionally by people at a crime scene are referred to as latent fingerprints . Most existing techniques to detect and lift latent fingerprints require application of certain material directly onto the exhibit. The chemical and physical processing applied onto the fingerprint potentially degrades or prevents further forensic testing on the same evidence sample. Many existing methods also come with deleterious side effects. We introduce a method to detect and extract latent fingerprint images without applying any powder or chemicals on the object. Our method is based on the optical phenomena of polarization and specular reflection together with the physiology of fingerprint formation. The recovered image quality is comparable to existing methods. In some cases like the sticky side of a tape our method shows unique advantages

Separation and contrast enhancement of overlapping cast shadow components using polarization

Shadow is an inseparable aspect of all natural scenes. When there are multiple light sources or multiple reflections several different shadows may overlap at the same location and create complicated patterns. Shadows are a potentially good source of information about a scene if the shadow regions can be properly identified and segmented. However, shadow region identification and segmentation is a difficult task and improperly identified shadows often interfere with machine vision tasks like object recognition and tracking. We propose here a new shadow separation and contrast enhancement method based on the polarization of light. Polarization information of the scene captured by our polarization-sensitive camera is shown to separate shadows from different light sources effectively. Such shadow separation is almost impossible to realize with conventional, polarization-insensitive imaging

Adaptive Algorithms for 2–Channel Polarization Sensing under Various Polarization Statistics with Non-Uniform Distributions

The polarization of light carries much useful information about the environment. Biological studies have shown that some animal species use polarization information for navigation and other purposes. It has been previously shown that a bio-inspired Polarization Difference Imaging technique can facilitate detection and feature extraction of targets in scattering media. It has also been established by S. Tyo1 that Polarization Sum and Polarization Difference are the optimum pair of linear combinations of images taken through two orthogonally oriented linear polarizers of a scene having a uniform distribution of polarization directions. However, in many real environments the scene has a non-uniform distribution of polarization directions. Using principal component analysis of the polarization statistics of the scene, here we develop a method to determine the two optimum information channels with unequal weighting coefficients that can be formed as linear combinations of the images of a scene taken through a pair of linear polarizers not constrained to the horizontal and vertical directions of the scene We determine the optimal orientations of linear polarization filters that enhance separation of a target from the background, where the target is defined as an area with distinct polarization characteristics as compared to the background. Experimental results confirm that in most situations adaptive polarization difference imaging outperforms conventional polarization difference imaging with fixed channels

Correction to: Comparative effectiveness and safety of non-vitamin K antagonists for atrial fibrillation in clinical practice: GLORIA-AF Registry

International audienceIn this article, the name of the GLORIA-AF investigator Anastasios Kollias was given incorrectly as Athanasios Kollias in the Acknowledgements. The original article has been corrected