Due to the modern advent of near ubiquitous accessibility to rapid international transportation the epidemiologic trends of highly communicable diseases can be devastating. With the recent emergence of diseases matching this pattern, such as Severe Acute Respiratory Syndrome (SARS), an area of overt concern has been the transmission of infection through respiratory droplets. Approved facemasks are typically effective physical barriers for preventing the spread of viruses through droplets, but breaches in a mask’s integrity can lead to an elevated risk of exposure and subsequent infection. Quality control mechanisms in place during the manufacturing process insure that masks are defect free when leaving the factory, but there remains little to detect damage caused by transportation or during usage. A system that could monitor masks in real-time while they were in use would facilitate a more secure environment for treatment and screening. To fulfill this necessity, we have devised a touchless method to detect mask breaches in real-time by utilizing the emissive properties of the mask in the thermal infrared spectrum. Specifically, we use a specialized thermal imaging system to detect minute air leakage in masks based on the principles of heat transfer and thermodynamics. The advantage of this passive modality is that thermal imaging does not require contact with the subject and can provide instant visualization and analysis. These capabilities can prove invaluable for protecting personnel in scenarios with elevated levels of transmission risk such as hospital clinics, border check points, and airports.
Face detection is an important prerequisite step for successful face
recognition. Face detection methods reported in the literature are far from perfect and deteriorate ungracefully where lighting conditions cannot be controlled. We propose a method that could potentially outperform state-of-the-art face detection methods in environments with dynamic lighting conditions. The approach capitalizes upon our near-IR skin and face detection methods reported elsewhere. It ascertains the existence of a face within a skin region by finding the eyes and eyebrows. The eye-eyebrow pairs are determined by extracting appropriate features from multiple near-IR bands. In this paper we introduce a novel feature extraction method we call dynamic integral projection. The method is relatively simple but highly effective because the processing is constrained within the skin region and aided by the near-IR phenomenology.