Projection functions are specific types of geometric feature-based approaches that are used in finding intensity variation in an image and extracting the feature vectors. Geng et al. [23] used the variance projection function for iris localization. Despite the wide application of VPF and MIPF (Mean Integral Projection Function), both have their limitations. MIPF will fail when vertical and horizontal summations of the elements in searching area are unchanged, while VPF will fail in case of the same variance and different mean of the elements. Therefore, the landmarks that have relatively high contrast cannot be properly extracted. To overcome these problems, a new projection function which we called General Projection Function (GPF) is proposed by Bastanfard and Dehshibi []. They apply GPF on Iranian Face Database to locate the position of the facial feature points such as the iris, nose, center of lips and chin. In order to increase the accuracy of feature localization in case of occlusions such as glass and scarf Dehshibi et al [] propose a new projection function called Combined P...
Biometrics-based authentication applications include workstation, network, and domain access, single sign-on, application logon, data protection, remote access to resources, transaction security and Web security (Campbell, 1995). Utilized alone or integrated with other technologies such as smart cards, encryption keys and digital signatures, biometrics are set to pervade nearly all aspects of the economy and our daily lives (Campbell, 1995). Among the features measured are; face, fingerprints, hand geometry, iris, and voice (Campbell, 1995).
describes the Contourlet transform and rotation-scale invariant texture representation. Section 4 contains the description of similarity measure for image retrieval. Simulation results in Section 5 will show the performance of our scheme. Finally,Section 6 concludes this presentation.
[5] W.Zhang, S.Shan, ”Local Gabor binary pattern histogram sequence (LGBPHS): a novel non-statistical model for face representation and recognition,” ICCV, vol. 1, pp.786-791, 2005.
The term biometrics is commonly known as the field of development of statistical and mathematical methods applicable to data analysis problems in the biological sciences. Though, even more recently it has taken on a whole new definition. Biometrics is an amazing new topic referring to “the emerging field of technology devoted to the identification of individuals using biological traits, based on retinal or iris scanning, fingerprints, or face recognition”. Biometrics has already begun using applications that range from attendance tracking with a time clock to security checkpoints with a large volume of people. The growing field of biometrics has really been put on the map by two things, the technological advances made within the last 20 years, and the growing risk of security and terrorism among people all over the world. In this paper I will focus on: the growing field of biometrics, why it is important to our future, how the United States government has played a role in its development and use, the risks involved, the implications on public privacy, and further recommendations received from all over the science and technology field.
A biometric recognition system can be used with a number of physiological characteristics (e.g. fingerprint, palmprint, hand geometry, face, iris, ear shape, and retina vein) and behavioral characteristics (e.g. gait, voice, signature and keystroke dynamics) to provide automatic identification of individuals based on their inherent physical and /or behavioral characteristics. Among these biometrics, iris recognition is one of the most accurate and reliable biometric for identification because of following characteristics (i) Iris pattern has complex and distinctive pattern such as arching ligaments, crypts, corona, freckles, furrows, ridges, rings and a zigzag collarette [1]. (ii) possess 266 degrees-of-freedom in variability and uniqueness in the order of one in 1072 [2].
When Maxwell Smart first whipped out his shoe phone in 1965, everyone saw an act of pure movie magic. Back in the mid to late 1900s everybody had the same idea of the future. Everyone pictured the future as talking robots (Siri), computerized pocket-sized dictionaries (smart-phones), hovering devices (drones), and much more. Today, everyone thinks of these technologies as commonalities. Most of these current devices have a valuable impact, while few create debatable issues. The company NGI has a system that will revolutionize the field of biometric facial recognition. In the article titled Embracing Big Brother: How Facial Recognition Could Help Fight Crime, author Jim Stenman says, "The mission is to reduce terrorist and criminal activity by improving and expanding biometric identification as well as criminal history information s...
I’m going to start off by stating that facial recognition has some benefits to offer for both businesses and consumers. Up until the last couple of years, this technology has been generally used by law enforcement to stop known criminals and for border control, but since then companies have shown more interest in using it for commercial uses. Companies
Feature extraction on the basis of principle lines: Any palm print have several principal lines in it, on the basis of these feature extraction is quiet useful for recognition and extraction of palm print recognition system.
[6] Rala M. Ebied,” Feature Extraction using PCA and Kernel-PCA for Face Recognition”, in The 8th International Conference on INFOrmatics and Systems Computational Intelligence and Multimedia Computing Track , 2012 ,pp mm72-mm77
Biometric technology is used for the ways humans can be identified by unique aspects of their bodies, such as fingerprints, body odor, our voices and many more. If one was to think about privacy rights, he/she would be concerned about the widespread adoption of these systems, since such systems could easily be used to develop a record of known rebellious people and/or dangerous criminals, to be used for social control purposes. Although that may seem pretty good and a positive thing for the society, one should take into account of the defects and errors of technology. Of the many biometrics technologies that are being developed and are already developed, facial recognition is one of the most threatening because it can be deployed secretly; one may not know whether or when they can be caught in a surveillance camera for such facial recognition biometrics. Additionally, tests have found that the miscalculations for facial biometrics technologies are very high. As a result, according to Privacy Rights Clearinghouse, innocent people can be erroneously identified as dangerous criminals and actual dangerous criminals and/or suspected terrorists can fail to be detected overall, allowing for a huge injustice and unfairness. Privacy rights concerned with biometrics have sparked a concern and should be dealt with; otherwise, this is just one of the
This project will mainly focus on face detection and feature extraction and only one webcam will be used and mounted on a laptop so that the image frame can be extracted out from the video. After we get the image, we will proceed to another stage which is face detection to detect the human face from that image frame.
Guided by my team’s Public Health Nurses and Managers, during my Integration Practicum I have increased my knowledge about the roles and responsibilities of public nurses related to Chronic Disease and Injury Prevention (CDIP) programs (Youth focus). I was working collaboratively with my CDIP Team to proactively contribute to the organization’s planning and implementation processes (such as meetings, professional events, various workshops, etc.). For example, I have revised and referenced the document about smoke- free housing in Ontario, as well as prepared presentation on the meeting related to the agency training workplans necessary for updating of Community/ School Consultation Tools. I was involved in a multidisciplinary
They also found that region based methods are also time consuming and not give effective segmentation. They proposed a new region based method based on Least Square method in order to detect objects sharply. They used a weight matrix for region based method which also takes the local information into account and also the usage of Least Square method provides optimal and fast segmentation. Comparison of their method is conducted with Otsu method and Chan-Vese method using Lena image. Their method can extract the features more accurately than other methods.
_ real-time spatialized audio or face and eye tracking or detection and tracking of human face,eyes and audio technology
Iris recognition is very accurate and distinctive because iris has a complex texture that can produce a substantial amount of information to identify a person. Furthermore, the iris remains almost unchanged from childhood, only minuscule variations are presented. The biometric data is captured using a small and high definition camera that is able to recognize different characteristics of the iris. Moreover, the system can detect the use of contact lens with a fake iris and can realize with the natural movement of the eye if the sample object is a living being. Although initially iris recognition systems were expensive and complex to use, new technology developments have improved these weaknesses.