An overview of spectral imaging of human skin toward face recognition

Abstract

Spectral imaging is a form of remote sensing that provides a means of collecting information from surroundings without physical contact. Differences in spectral reflectance over the electromagnetic spectrum allow for the detection, classification, or quantification of objects in a scene. The development of this field has largely benefited from Earth observing airborne and spaceborne programs. Information gained from spectral imaging has been recognized as making key contributions from the regional to the global scale. The burgeoning market of compact hyperspectral sensors has opened new opportunities, at smaller spatial scales, in a large number of applications such as medical, environmental, security, and industrial processes. The market is expected to continue to evolve and result in advancements in sensor size, performance, and cost. In order to employ spectral imaging for a specific task, it is critical to have a fundamental understanding of the phenomenology of the subject of interest, the imaging sensor, image processing, and interpretation of the results. Spectral imaging of human tissue has the strong foundation of a well-known combination of components, e.g., hemoglobin, melanin, and water that make skin distinct from most backgrounds. These components are heterogeneously distributed and vary across the skin of individuals and between individuals. The spatial component of spectral imaging provides a basis for making spectral distinctions of these differences. This chapter provides an introduction to the interaction of energy in the electromagnetic spectrum with human tissue and other materials, the fundamentals of sensors and data collection, common analysis techniques, and the interpretation of results for decision making. The basic information provided in this chapter can be utilized for a wide range of applications where spectral imaging may be adopted including face recognition.