Recognizing people by their ear has recently received significant attention in the literature. Several reasons account for this trend: first, ear recognition does not suffer from some problems associated with other noncontact biometrics, such as face recognition; second, it is the most promising candidate for combination with the face in the context of multi-pose face recognition; and third, the ear can be used for human recognition in surveillance videos where the face may be occluded completely or in part. Further, the ear appears to degrade little with age. Even though current ear detection and recognition systems have reached a certain level of maturity, their success is limited to controlled indoor conditions. In addition to variation in illumination, other open research problems include hair occlusion, earprint forensics, ear symmetry, ear classification, and ear individuality.This article provides a detailed survey of research conducted in ear detection and recognition. It provides an up-to-date review of the existing literature revealing the current state-of-art for not only those who are working in this area but also for those who might exploit this new approach. Furthermore, it offers insights into some unsolved ear recognition problems as well as ear databases available for researchers.
A multi-stage Synthetic Aperture Radar (SAR) Automatic Target Recognition (ATR) system is analyzed across images of various pixel areas achieved by both square and non-square resolution. Non-square resolution offers the ability to achieve finer resolution in the range or cross-range direction with a corresponding degradation of resolution in the crossrange or range direction, respectively. The algorithms examined include a standard 2-parameter Constant False Alarm Rate (CFAR) detection stage, a discrimination stage, and a template-based classification stage. Performance for each stage with respect to both pixel area and square versus non-square resolution is shown via cascaded Receiver Operating Characteristic (ROC) curves. The results indicate that, for fixed pixel areas, non-square resolution imagery can achieve statistically similar performance to square pixel resolution imagery in a multi-stage SAR ATR system.
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