Surgical Embryology

Davis, Jack E.

doi:10.1007/978-1-4613-9999-5_5

Cited by 7 publications

(23 citation statements)

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“…They are more clearly illustrated in the drawing (b) [69]. (c) Mandibular and Hyoid hillocks [23] his findings are still viable. His proposed arrangement is mainly based on his step-by-step observations of ear development (figure 4.5(b)).…”

Section: Hillocks Hypothesismentioning

confidence: 99%

“…Better understanding of these anomalies leads to better surgical procedures to correct them, as noted by Davis [23]. He reviewed numerous congenital external ear defects and assigned their causes to anomalies in the development of different hillocks.…”

Section: Motivationsmentioning

confidence: 99%

“…In their study, they did not show much concern for the fate of the hyoid hillocks (4, 5 and 6). Davis [23] studied a wide range of congenital malformations of the external ear, and assigned the cause of every abnormality to defects of the auricular hillocks, in an attempt which was described by Hunter et al [35] as 'speculative' (figure 4.5(d)). Sulik [72] studied the scanning electron micrographs of human embryos (figure 4.5(f)).…”

Section: Hillocks Hypothesismentioning

confidence: 99%

“…In this section, we concentrate on anomalies which indicate specific individual components or hint as to the sites of big variations. For more information on these defects see [35] and [23].…”

Section: Variations and Anomaliesmentioning

confidence: 99%

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On guided model-based analysis for ear biometrics

Arbab-Zavar

Nixon

2011

Computer Vision and Image Understanding

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Ears are a new biometric with major advantage in that they appear to maintain their structure with increasing age. Current approaches have exploited 2D and 3D images of the ear in human identification. Contending that the ear is mainly a planar shape we use 2D images, which are consistent with deployment in surveillance and other planarimage scenarios. So far ear biometric approaches have mostly used general properties and overall appearance of ear images in recognition, while the structure of the ear has not been discussed. In this thesis, we propose a new model-based approach to ear biometrics. Our model is a part-wise description of the ear structure. By embryological evidence of ear development, we shall show that the ear is indeed a composite structure of individual components. Our model parts are derived by a stochastic clustering method on a set of scale invariant features on a training set. We shall review different accounts of ear formation and consider some research into congenital ear anomalies which discuss apportioning various components to the ear's complex structure. We demonstrate that our model description is in accordance with these accounts. We extend our model description, by proposing a new wavelet-based analysis with a specific aim of capturing information in the ear's outer structures. We shall show that this section of the ear is not sufficiently explored by the model, while given that it exhibits large variations in shape, intuitively, it is significant to the recognition process. In this new analysis, log-Gabor filters exploit the frequency content of the ear's outer structures.In recognition, ears are automatically enrolled via our new enrolment algorithm, which is based on the elliptical shape of ears in head profile images. These samples are then recognized via the parts selected by the model. The incorporation of the wavelet-based analysis of the outer ear structures forms an extended or hybrid method. The performance is evaluated on test sets selected from the XM2VTS database. By results, both ii in modelling and recognition, our new model-based approach does indeed appear to be a promising new approach to ear biometrics. In this, the recognition performance has improved notably by the incorporation of our new wavelet-based analysis.The main obstacle hindering the deployment of ear biometrics is the potential occlusion by hair. A model-based approach has a further attraction, since it has an advantage in handling noise and occlusion. Also, by localization, a wavelet can offer performance advantages when handling occluded data. A robust matching technique is also added to restrict the influence of corrupted wavelet projections. Furthermore, our automatic enrolment is tolerant of occlusion in ear samples. We shall present a thorough evaluation of performance in occlusion, using PCA and a robust PCA for comparison purposes. Our hybrid method obtains promising results recognizing occluded ears. Our results have confirmed the validity of this approach both in modelling and recognition. ...

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Section: Hillocks Hypothesismentioning

confidence: 99%

Section: Motivationsmentioning

confidence: 99%

Section: Hillocks Hypothesismentioning

confidence: 99%

Section: Variations and Anomaliesmentioning

confidence: 99%

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On guided model-based analysis for ear biometrics

Arbab-Zavar

Nixon

2011

Computer Vision and Image Understanding

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“…[4], I-Chuan [5], Nixon [6], etc. Pursuant to these studies, due to ear's special shape and appearance, it is unique for human recognition.…”

Section: Introductionmentioning

confidence: 99%

An Ear Recognition Method Based on Rotation Invariant Transformed DCT

Hourali

Gharravi

2017

IJECE

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Human recognition systems have gained great importance recently in a wide range of applications like access, control, criminal investigation and border security. Ear is an emerging biometric which has rich and stable structure and can potentially be implemented reliably and cost efficiently. Thus human ear recognition has been researched widely and made greatly progress. High recognition rates which are reported in most existing methods can be reached only under closely controlled conditions. Actually a slight amount of rotation and translation which is inescapable would be injurious for system performance. In this paper, a method that uses a transformed type of DCT is implemented to extract meaningful features from ear images. This algorithm is quite robust to ear rotation, translation and illumination. The proposed method is experimented on two popular databases, i.e. USTB II and IIT Delhi II, which achieves significant improvement in the performance in comparison to other methods with good efficiency based on LBP, DSIFT and Gabor. Also because of considering only important coefficients, this method is faster compared to other methods.

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