Description: 便于使用的收集人脸图像建立数据库的工具程序。供人脸检测/识别/表情/姿态等模式识别、人工智能领域的研究者使用。可以方便地从网页中收集人脸照片，提供良好的交互界面对照片在模式识别，尤其是biometric领域中所需的各种属性进行标注，建立数据库。-easy-to-use collection of facial image database tools procedures. For Face detection / identification / expression / gestures, such as pattern recognition, artificial intelligence researchers in the field use. Can easily collected from the website pictures of faces with a good interface for photos in pattern recognition, particularly biometric field for the various attributes tagging, the establishment of databases. Platform: |
Size: 60838 |
Author:冯雪涛 |
Hits:
Description: 便于使用的收集人脸图像建立数据库的工具程序。供人脸检测/识别/表情/姿态等模式识别、人工智能领域的研究者使用。可以方便地从网页中收集人脸照片，提供良好的交互界面对照片在模式识别，尤其是biometric领域中所需的各种属性进行标注，建立数据库。-easy-to-use collection of facial image database tools procedures. For Face detection/identification/expression/gestures, such as pattern recognition, artificial intelligence researchers in the field use. Can easily collected from the website pictures of faces with a good interface for photos in pattern recognition, particularly biometric field for the various attributes tagging, the establishment of databases. Platform: |
Size: 60416 |
Author:冯雪涛 |
Hits:
Description: 生物特征识别技术是为了进行身份验证而采用自动技术测量其身体特征或是个人行为特点，并将这些特征或特点与数据库的模板数据进行比较，完成认证的一种解决方案。-Biometric identification technology is in order to authenticate the use of automatic measurement of its physical characteristics or personal behavior characteristics, and these features or characteristics of the template and database data to complete the certification of a solution. Platform: |
Size: 386048 |
Author: |
Hits:
Description: 人脸识别特指利用分析比较人脸视觉特征信息进行身份鉴别的计算机技术。人脸识别是一项热门的计算机技术研究领域，它属于生物特征识别技术，是对生物体（一般特指人）本身的生物特征来区分生物体个体。一般来说，人脸识别系统包括图像摄取、人脸定位、图像预处理、以及人脸识别（身份确认或者身份查找）。系统输入一般是一张或者一系列含有未确定身份的人脸图像，以及人脸数据库中的若干已知身份的 人脸识别人脸图象或者相应的编码，而其输出则是一系列相似度得分，表明待识别的人脸的身份。-Face Recognition refers specifically to take advantage of the analysis and comparison of face visual feature information for the identification of computer technology. Face recognition is a popular research field of computer technology, it belongs to biometric identification technology, is to distinguish between organisms of individual organisms (usually unspecified) itself biometric. In general, the face recognition system includes an image pickup face positioning, image pre-processing, as well as face recognition (identification or identity lookup). System input is generally one or a series of face image containing undetermined identity, as well as a number of known identity in the face database of face recognition face image encoding, and its output is a series of similarity score, indicate that the identity of the human face to be identified. Platform: |
Size: 131072 |
Author:古志榮 |
Hits:
Description: Iris Recognition is a rapidly expanding method of biometric authentication that uses
pattern-recognition techniques on images of irides to uniquely identify an individual.
Algorithms produced by Professor John Daugman [1] have proven to be increasingly accurate
and reliable after over 200 billion comparisons [2]. The aim of this group project
is to implement a working prototype of the techniques and methods used for iris recognition,
and to test these methods on a database of irides provided by the Chinese Academy
of Sciences Institute of Automation (CASIA) [3], which consists of 756 images of irides
from 108 individuals-Iris Recognition is a rapidly expanding method of biometric authentication that uses
pattern-recognition techniques on images of irides to uniquely identify an individual.
Algorithms produced by Professor John Daugman [1] have proven to be increasingly accurate
and reliable after over 200 billion comparisons [2]. The aim of this group project
is to implement a working prototype of the techniques and methods used for iris recognition,
and to test these methods on a database of irides provided by the Chinese Academy
of Sciences Institute of Automation (CASIA) [3], which consists of 756 images of irides
from 108 individuals Platform: |
Size: 1153024 |
Author:Mohammad |
Hits:
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 . Platform: |
Size: 247808 |
Author:krish |
Hits:
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. Platform: |
Size: 247808 |
Author:krish |
Hits:
Search - biometric database