Ear Biometrics Based on Geometrical Feature Extraction

Biometrics identification methods proved to be very efficient, more natural and easy for users than traditional methods of human identification. In fact, only biometrics methods truly identify humans, not keys and cards they posses or passwords they should remember. The future of biometrics will surely lead to systems based on image analysis as the data acquisition is very simple and requires only cameras, scanners or sensors. More importantly such methods could be passive, which means that the user does not have to take active part in the whole process or, in fact, would not even know that the process of identification takes place. There are many possible data sources for human identification systems, but the physiological biometrics seem to have many advantages over methods based on human behaviour. The most interesting human anatomical parts for such passive, physiological biometrics systems based on images acquired from cameras are face and ear. Both of those methods contain large volume of unique features that allow to distinctively identify many users and will be surely implemented into efficient biometrics systems for many applications. The article introduces to ear biometrics and presents its advantages over face biometrics in passive human identification systems. Then the geometrical method of feature extraction from human ear images in order to perform human identification is presented

The effect of time on ear biometrics

We present an experimental study to demonstrate the effect of the time difference in image acquisition for gallery and probe on the performance of ear recognition. This experimental research is the first study on the time effect on ear biometrics. For the purpose of recognition, we convolve banana wavelets with an ear image and then apply local binary pattern on the convolved image. The histograms of the produced image are then used as features to describe an ear. A histogram intersection technique is then applied on the histograms of two ears to measure the ear similarity for the recognition purposes. We also use analysis of variance (ANOVA) to select features to identify the best banana wavelets for the recognition process. The experimental results show that the recognition rate is only slightly reduced by time. The average recognition rate of 98.5% is achieved for an eleven month-difference between gallery and probe on an un-occluded ear dataset of 1491 images of ears selected from Southampton University ear database

Visualization of the Membranous Labyrinth and Nerve Fiber Pathways in Human and Animal Inner Ears Using MicroCT Imaging

Design and implantation of bionic implants for restoring impaired hair cell function relies on accurate knowledge about the microanatomy and nerve fiber pathways of the human inner ear and its variation. Non-destructive isotropic imaging of soft tissues of the inner ear with lab-based microscopic X-ray computed tomography (microCT) offers high resolution but requires contrast enhancement using compounds with high X-ray attenuation. We evaluated different contrast enhancement techniques in mice, cat, and human temporal bones to differentially visualize the membranous labyrinth, sensory epithelia, and their innervating nerves together with the facial nerve and middle ear. Lugol’s iodine potassium iodine (I2KI) gave high soft tissue contrast in ossified specimens but failed to provide unambiguous identification of smaller nerve fiber bundles inside small bony canals. Fixation or post-fixation with osmium tetroxide followed by decalcification in EDTA provided superior contrast for nerve fibers and membranous structures. We processed 50 human temporal bones and acquired microCT scans with 15 μm voxel size. Subsequently we segmented sensorineural structures and the endolymphatic compartment for 3D representations to serve for morphometric variation analysis. We tested higher resolution image acquisition down to 3.0 μm voxel size in human and 0.5 μm in mice, which provided a unique level of detail and enabled us to visualize single neurons and hair cells in the mouse inner ear, which could offer an alternative quantitative analysis of cell numbers in smaller animals. Bigger ossified human temporal bones comprising the middle ear and mastoid bone can be contrasted with I2KI and imaged in toto at 25 μm voxel size. These data are suitable for surgical planning for electrode prototype placements. A preliminary assessment of geometric changes through tissue processing resulted in 1.6% volume increase caused during decalcification by EDTA and 0.5% volume increase caused by partial dehydration to 70% ethanol, which proved to be the best mounting medium for microCT image acquisition

The ear as a biometric

It is more than 10 years since the first tentative experiments in ear biometrics were conducted and it has now reached the “adolescence” of its development towards a mature biometric. Here we present a timely retrospective of the ensuing research since those early days. Whilst its detailed structure may not be as complex as the iris, we show that the ear has unique security advantages over other biometrics. It is most unusual, even unique, in that it supports not only visual and forensic recognition, but also acoustic recognition at the same time. This, together with its deep three-dimensional structure and its robust resistance to change with age will make it very difficult to counterfeit thus ensuring that the ear will occupy a special place in situations requiring a high degree of protection