How re-training process affect the performance of no-reference image quality metric for face images
0
Citation
0
Reference
10
Related Paper
Abstract:
The accuracy of face recognition systems is significantly affected by the quality of face sample images. There are many existing no-reference image quality metrics (IQMs) that are able to assess natural image quality by taking into account similar image-based quality attributes. Previous study showed that IQMs can assess face sample quality according to the biometric system performance. In addition, re-training an IQM can improve its performance for face biometric images. However, only one database was used in the previous study, and it contains only image-based distortions. In this paper, we propose to extend the previous study by use multiple face database including FERET color face database, and apply multiple setups for the re-training process in order to investigate how the re-training process affect the performance of no-reference image quality metric for face biometric images. The experimental results show that the performance of the appropriate IQM can be improved for multiple databases, and different re-training setups can influence the IQM’s performance.Keywords:
Sample (material)
Biometric computing aims to automatically sensing and analyzing the biometric trait,learning models of personal identification,emotion and behavior analysis,healthy condition analysis and aesthetic evaluation using biometric data.Based on the authors' experience on biometric comput-ing research,this paper provides a personal survey on the progress in biometric recognition,medical biometric computing,and aesthetic biometric computing.
Biometric data
Identification
Cite
Citations (0)
Word error rate
Cite
Citations (83)
An automized verification of an individual from biometric features that are extracted from the behavioral or physical characteristics. The verification system can easily discriminate between a permitted person and an intruder. The biometric system is using biometrics attributes rather than ID card or password. The uses of biometrics can be found in personal computers, banks, ATMs, credit cards, cell phones, social and health services. In the future, biometrics may use more than one type of biometrics attributes rather than using the single one. Unimodal biometrics has some problems with the features. In this paper, some unimodal biometrics is presented.
Biometric data
Hand geometry
Cite
Citations (0)
Now day’s security of any area is most important task. At different places security required authentication for that purpose biometric system is commonly used. Biometrics is the most suitable means of identifying and authenticating individuals in a reliable and fast way through unique biological characteristics. In this paper we study some concepts which are related to biometrics like meaning of biometrics, history of biometrics, biometric verification and identification, Biometric Recognition techniques, uses, advantages, disadvantages of biometrics. In the current research work we are focus different types of biometric system with its advantages and disadvantageous.
Identification
Cite
Citations (0)
In todays environment, biometric are play important role for the security purpose .with the help of different type of biometric thief can be easily caught. Various type of physical and behavioral biometric used for the authentication and identification purpose. Physical biometric are most popular and give the highest accuracy rather than behavioral biometric. These biometric are used according to requirement like field where we want to use, cost, and accuracy. Different special devices are needed for using the different biometric. In this paper shows different types of biometric are available in the world with their merits and demerits.
Identification
Biometric data
Cite
Citations (0)
Face recognition is a technique used for identify identity by analyzing face images and distilling effective recognition information from face images.This article presented an arithmetic of face recognition based on eigenfaces,gave the explaination of eigenface,and made a simulation of DRL face database by using program baced on OpenCV.This method recognizes and classifies face images by computing the space distance between face image and eigenfaces,and it can recognize face image quickly and exactly.
Eigenface
Three-dimensional face recognition
Cite
Citations (0)
Biometrics is become a necessary technology in today's world. Research is rapidly growing in the field of biometrics. This paper gives the overview of the major Biometric Technologies which is well proven versus Electrocardiogram as biometric authentication tool. A researcher who is planning to work on Biometrics field could use this paper for understanding various biometrics technologies and how biomedicai signal can be interpolated to biometric authentication tool.
Cite
Citations (0)
Many biometrics requirements have led to the extensive study of biometric technologies and the development of numerous algorithms, applications, and systems, which could be defined as Biometrics Computing. This presentation will systematically explain this new research trend. As case studies, a new biometrics technology (palmprint recognition) and two new biometrics applications (medical biometrics and aesthetical biometrics), are introduces. Based on over ten years' experiences, many useful results could be given to illustrate their effectiveness.
Presentation (obstetrics)
Cite
Citations (0)
An approach to the detection and identification of human faces is presented, and a working, near-real-time face recognition system which tracks a subject's head and then recognizes the person by comparing characteristics of the face to those of known individuals is described. This approach treats face recognition as a two-dimensional recognition problem, taking advantage of the fact that faces are normally upright and thus may be described by a small set of 2-D characteristic views. Face images are projected onto a feature space ('face space') that best encodes the variation among known face images. The face space is defined by the 'eigenfaces', which are the eigenvectors of the set of faces; they do not necessarily correspond to isolated features such as eyes, ears, and noses. The framework provides the ability to learn to recognize new faces in an unsupervised manner.< >
Eigenface
Three-dimensional face recognition
Feature (linguistics)
Feature vector
Cite
Citations (5,348)
Most of the biometric research being done is for adults and the identification accuracy of newborn are least reported in the literatures. In this paper we propose a novel biometric identification method for newborn babies using their face and soft biometrics. Accurate patient identification (ID) is essential for patient safety, especially with our smallest and most vulnerable pediatric patients. The main contribution of the research are (a) the preparation of face and soft biometric database of newborn. (b) Testing the algorithm for identification of 210 newborn. The combined use of all the four soft biometric traits results in an improvement of approximately 6% over the primary biometric system.
Identification
Cite
Citations (15)