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Description: 人耳识别技术是20世纪90年代末开始兴起的一种生物特征识别技术，与其它生物特征识别技术比较具有以下几个特点：（1）与人脸识别方法比较，耳识别方法不受面部表情、化妆品和胡须变化的影响，同时保留了面部识别图象采集方便的优点，与人脸相比，整个人耳的颜色更加一致、图像尺寸更小，数据处理量也更小。（2）与指纹识别方法比较，耳图象的获取是一种被动方式，即通过非接触方式获取耳图像，不存在通过接触传染疾病的机会，因此，其信息获取方式具有容易被人接受的优点。（3）与虹膜识别方法比较，首先，由于人脸和头发的存在，需要在耳识别过程中增加一个耳区域定位步骤，这并不影响耳特征的提取，而眼毛对虹膜的遮挡将直接影响虹膜特征的提取。头发对于耳的遮挡可以容易地避免，而眼毛对于虹膜的遮挡是生理结构决定的，也是难以避免的。其次，就目前的技术而言，虹膜采集需要测试者与采集装置之间的位置在机器发出的语言提示下进行不断地调整，同时要瞪大眼睛，使虹膜尽可能暴露，初试者通常要反复多次调整才能够达到要求，而耳采集方式与脸采集方式基本相同，测试者很容易达到拍摄图象的要求条件。最后，虹膜采集装置的成本要高于耳采集装置。-ear recognition technology of the 20th century, the beginning of the end of the 1990s the rise of a biometric identification technology, and other biometric identification technology compared with the following characteristics : (1) and face recognition methods, Ear Recognition from facial expressions, cosmetics and beards change, while retaining a facial recognition image acquisition convenience advantages, and face, the ears of the whole person more consistent color. Image size is smaller, the amount of data processing are even smaller. (2) and fingerprint identification methods, the ear image acquisition is a passive way, through non-contact ear acquire images, and there is no disease transmitted by the opportunity, therefore, its way to obtain information is easily accepted advantages.
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Size: 202988 |
Author: 蒋建军 |
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Description: 人耳识别技术是20世纪90年代末开始兴起的一种生物特征识别技术，与其它生物特征识别技术比较具有以下几个特点：（1）与人脸识别方法比较，耳识别方法不受面部表情、化妆品和胡须变化的影响，同时保留了面部识别图象采集方便的优点，与人脸相比，整个人耳的颜色更加一致、图像尺寸更小，数据处理量也更小。（2）与指纹识别方法比较，耳图象的获取是一种被动方式，即通过非接触方式获取耳图像，不存在通过接触传染疾病的机会，因此，其信息获取方式具有容易被人接受的优点。（3）与虹膜识别方法比较，首先，由于人脸和头发的存在，需要在耳识别过程中增加一个耳区域定位步骤，这并不影响耳特征的提取，而眼毛对虹膜的遮挡将直接影响虹膜特征的提取。头发对于耳的遮挡可以容易地避免，而眼毛对于虹膜的遮挡是生理结构决定的，也是难以避免的。其次，就目前的技术而言，虹膜采集需要测试者与采集装置之间的位置在机器发出的语言提示下进行不断地调整，同时要瞪大眼睛，使虹膜尽可能暴露，初试者通常要反复多次调整才能够达到要求，而耳采集方式与脸采集方式基本相同，测试者很容易达到拍摄图象的要求条件。最后，虹膜采集装置的成本要高于耳采集装置。-ear recognition technology of the 20th century, the beginning of the end of the 1990s the rise of a biometric identification technology, and other biometric identification technology compared with the following characteristics : (1) and face recognition methods, Ear Recognition from facial expressions, cosmetics and beards change, while retaining a facial recognition image acquisition convenience advantages, and face, the ears of the whole person more consistent color. Image size is smaller, the amount of data processing are even smaller. (2) and fingerprint identification methods, the ear image acquisition is a passive way, through non-contact ear acquire images, and there is no disease transmitted by the opportunity, therefore, its way to obtain information is easily accepted advantages.
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Size: 202752 |
Author: 蒋建军 |
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Description: ImagesIEEE上的论文有关图像处理的论文：走向快速3D耳识别现实生活中的应用生物识别技术
-TOWARDS FAST 3D EAR RECOGNITION FOR
REAL-LIFE BIOMETRIC APPLICATIONS
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Size: 561152 |
Author: 王景涛 |
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Description: biometric ear recognition system
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Size: 481280 |
Author: dr_dos_ok |
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Description: biometric ear recognition documentation
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Size: 391168 |
Author: dr_dos_ok |
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Description: Ear Biometric An Aid to Personal Identification
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Size: 16384 |
Author: erfd |
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Description: program on image processing based on MATLAB for biometric recognition
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Size: 3072 |
Author: arti |
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Description: Try a simple experiment, try to visualize what your ears look like. You were not able
to? Well, then try to describe the ears of someone you see everyday. You will find
that even if you are looking directly at someone s ears, they are still difficult to
describe. We simply do not have the vocabulary for it our everyday language
provides only a few adjectives which can be applied to ears, all of which are generic
adjectives like large or floppy and not ones which are solely^ used to describe ears.
On the other hand, we are all capable of describing the faces of even briefly glimpsed
strangers with significant detail to allow police artists to reconstruct remarkable
resemblances of them. Even though we apparently lack the means to recognize one
another from our ears, we will see that the rich structure of the ear is unique and that it
can be used as an effective biometric for passive identification.-Try a simple experiment, try to visualize what your ears look like. You were not able
to? Well, then try to describe the ears of someone you see everyday. You will find
that even if you are looking directly at someone s ears, they are still difficult to
describe. We simply do not have the vocabulary for it our everyday language
provides only a few adjectives which can be applied to ears, all of which are generic
adjectives like large or floppy and not ones which are solely^ used to describe ears.
On the other hand, we are all capable of describing the faces of even briefly glimpsed
strangers with significant detail to allow police artists to reconstruct remarkable
resemblances of them. Even though we apparently lack the means to recognize one
another from our ears, we will see that the rich structure of the ear is unique and that it
can be used as an effective biometric for passive identification.
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Size: 1013760 |
Author: ismaail |
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Description: 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.
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Size: 529408 |
Author: ismaail |
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Description: 人耳识别功能，可以处理人耳图像并且识别出来，是一种生物识别技术-Ear Recognition function that can handle images and identified the human ear, is a biometric technology
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Size: 8696832 |
Author: harry |
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Description: The ear, as a biometric, has been given less
attention, compared to other biometrics such as fingerprint,
face and iris. Since it is a relatively new biometric, no
commercial applications involving ear recognition are
available. Intensive research in this field is thus required to
determine the feasibility of this biometric. In medical field,
especially in case of accidents and death, where face of patients
cannot be recognized, the use of ear can be helpful. In this
work, yet another method of recognizing people through their
ears is presented. Local Binary Patterns (LBP) is used as
features and the results are compared with that of Principal
Components Analysis (PCA). LBPhas a high discriminative
power, tolerance against globalillumination changes and low
computational load. Experiments were done on the Indian
Institute of Technology (IIT) Delhi ear image database and
results show that LBP yields a recognition rate of 93 while
PCA gives only 85 .-The ear, as a biometric, has been given less
attention, compared to other biometrics such as fingerprint,
face and iris. Since it is a relatively new biometric, no
commercial applications involving ear recognition are
available. Intensive research in this field is thus required to
determine the feasibility of this biometric. In medical field,
especially in case of accidents and death, where face of patients
cannot be recognized, the use of ear can be helpful. In this
work, yet another method of recognizing people through their
ears is presented. Local Binary Patterns (LBP) is used as
features and the results are compared with that of Principal
Components Analysis (PCA). LBPhas a high discriminative
power, tolerance against globalillumination changes and low
computational load. Experiments were done on the Indian
Institute of Technology (IIT) Delhi ear image database and
results show that LBP yields a recognition rate of 93 while
PCA gives only 85 .
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Size: 247808 |
Author: krish |
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Description: Previous works have shown that the ear is a promising candidate for biometric identification. However, in prior work, the
preprocessing of ear images has had manual steps and algorithms have not necessarily handled problems caused by hair and
earrings. We present a complete system for ear biometrics, including automated segmentation of the ear in a profile view image and
3D shape matching for recognition. We evaluated this system with the largest experimental study to date in ear biometrics, achieving a
rank-one recognition rate of 97.8 percent for an identification scenario and an equal error rate of 1.2 percent for a verification scenario
on a database of 415 subjects and 1,386 total probes.
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Size: 247808 |
Author: krish |
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Description: Using SIFT Algorithm for Verification of Ear Biometric
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Size: 1092608 |
Author: LALIT BHANWRELA |
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Description: 人耳识别作为一种新的生物特征识别技术在近两年来受到了越来越多的关注,人耳识别的研究使计算机根据人耳辨别人物身份成为可能。目前国内和国际上对此的研究还很少,还没有形成一套完整的识别体系。同人脸、虹膜和指纹等识别技术相比,人耳识别又具有其自身的独特性和研究价值。其研究内容主要涉及到人耳图像的采集、定位和分割、特征提取、模板匹配以及多模态融合等。-Ear recognition as a new biometric identification technology has received more and more attention in the past two years, the research of ear recognition makes it possible to recognize the identity of the computer according to the human ear. At present, there is little research on this country and the world, but it has not yet formed a complete set of recognition system. Compared with recognition technology of human face, iris and fingerprint, human ear recognition has its own uniqueness and research value. The main contents of the research are the acquisition, location and segmentation, feature extraction, template matching and multimodal fusion of human ear images.
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Size: 295936 |
Author: 王近两 |
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