Abstract
Ear biometrics, compared with other physical traits, presents both advantages and limits. First of all, the small surface and the quite simple structure play a controversial role. On the positive side, they allow faster processing than, say, face recognition, as well as less complex recognition strategies than, say, fingerprints. On the negative side, the small ear area itself makes recognition systems especially sensitive to occlusions. Moreover, the prominent 3D structure of distinctive elements like the pinna and the lobe makes the same systems sensible to changes in illumination and viewpoint. Overall, the best accuracy results are still achieved in conditions that are significantly more favorable than those found in typical (really) uncontrolled settings. This makes the use of this biometrics in real world applications still difficult to propose, since a commercial use requires a much higher robustness. Notwithstanding the mentioned limits, ear is still an attractive topic for biometrics research, due to other positive aspects. In particular, it is quite easy to acquire ear images remotely, and these anatomic features are also relatively stable in size and structure along time. Of course, as any other biometric trait, they also call for some template updating. This is mainly due to age, but not in the commonly assumed way. The apparent bigger size of elders' ears with respect to those of younger subjects, is due to the fact that aging causes a relaxation of the skin and of some muscle-fibrous structures that hold the so called pinna, i.e. the most evident anatomical element of the ear. This creates the belief that ears continue growing all life long. On the other hand, a similar process holds for the nose, for which the relaxation of the cartilage tissue tends to cause a curvature downwards. In this chapter we will present a survey of present techniques for ear recognition, from geometrical to 2D-3D multimodal, and will attempt a reasonable hypothesis about the future ability of ear biometrics to fulfill the requirements of less controlled/covert data acquisition frameworks.
