Current research is focused upon using a technique known as “Eigenears”, which is based upon the different structures of the outer ear. Eigenears is very similar to the technique of “Eigenfaces” used in facial recognition. Thus far, there are positive results in the scientific community that the outer ear is unique in its overall shape, in terms of depth, angular structure, and the overall formation of the earlobe structure.
From within this, scientists are currently examining the distances between the regions of the ear, in a forty five degree and 3-dimensional angular models. The raw data of the ear can be captured by taking an actual picture of the outer ear, preferably when the ear is placed against a glass platen in order to capture the actual, raw images. These raw images are then used for unique feature extraction and biometric template creation. Either a 3-dimensional or a thermal picture can be taken of the outer ear, with preference being given to the latter.
At the present time, there are two methodologies which are currently being examined for potential earlobe recognition, and they are:
- Principal Component Analysis: With this technique, the raw image of the ear is cropped, it is then scaled to a regular size, thus capturing the two keypoints of the ear, specifically the regions known as the triangular fossa and the antiragus, from which the unique features can be extracted from;
- 3-Dimensional Analysis: With this technique, the outer image of the ear is captured, thus ascertaining both the depth and the color type of the ear. Both the helix and the antihelix are examined, from which the unique features can be captured from.
Earlobe Recognition: The Advantages & The Disadvantages
Also, the potential of earlobe recognition can also be examined from the same seven criterion that all of the other biometric technologies in this chapter have been analyzed against:
- Universality: For the most part, unless an individual has a physical injury which caused them to have an absence of the ear, most people have an ear which can be examined for unique features;
- Uniqueness: Although it is still not yet proven scientifically, preliminary results have shown that the two tests involving 10,000 earlobes and identical twins, all individuals were to have found to each to possess a unique ear structure;
- Permanence: The shape of the ear more or less stays the same over the lifetime of an individual;
- Collectability: Certain variables from the external environment can certainly impact the capture of the raw images of the ear, and these variables include different types and kinds of lighting situations, jewelry such as the wearing of earrings, and wireless device accessories which can be placed in the outer ear;
- Performance: It is still too early to determine how well earlobe recognition will actually be adopted and used in the commercial market;
- Acceptability: Earlobe recognition is deemed to be a potentially non intrusive type of potential biometric technology, thus there should be no issues with regards to privacy rights;
- Resistance to circumvention: At this point, it is difficult to determine to determine this, but it is possible to construct a false earlobe.
Since there are no commercial applications yet of earlobe recognition, in the future, it is heavily anticipated that it will work well with facial recognition systems, in multimodal biometric solution applications.
Finally, of the three potential biometric technologies covered in this chapter, gait recognition appears to offer most potential in terms of practical deployment. It’s potential is very strong for multi-modal security applications. Think, for example, of a dual-level verification system whereby a subject’s identity is initially established on the basis of, for example, a fingerprint before being verified using gait recognition. It is also useful for one-to- may verification requirements at, for example, airports.
Under these conditions, gait recognition can offer significant time savings by allowing large groups of people to be identified in a single environment. Compared to gait recognition, earlobe recognition has much further to go, also in terms of research and development. This also applies to DNA recognition, even though it has the potential to be the best biometric of all (on account of its uniqueness).