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Facial Recognition Software And Security
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One of the grand challenges for computational intelligence and biometrics is to understand how people process and recognise faces and to develop automated and reliable systems. Biometrics has become the major component in the complex decision making process associated with security applications. The face detection and authentication challenges addressed include cluttered environments, image variability, occlusion and disguise, and temporal changes all within open set recognition.
Information and communication technologies are increasingly entering in all aspects of our life and in all sectors, opening a world of unprecedented scenarios where people interact with electronic devices embedded in environments that are sensitive and responsive to the presence of users.
Recognition of faces through computerization methods, has recently received significant attention. It plays an important role in many application areas such as, human-machine interaction, authentication and surveillance. However, the problem of machine recognition of human faces continues to attract researchers from disciplines such as image processing, pattern recognition, neutral networks, computer vision, computer graphics, and psychology.
Over the last ten years or so, this has become a popular area of research in computer vision and one of the most successful applications of image analysis and understanding. Because of the nature of the problem, not only computer science or researchers are interested in it, but neuroscientists and psychologists also. It is the general opinion that advances in computer vision research will provide useful insights to neuroscientists and psychologists into how human brain works, and vice versa.
Recognising a face is a task humans perform remarkably easily and successfully. This apparent simplicity has been researched to be performed artificially through computers but cannot claim to measure to human performance. More than 20 years of extensive research has been dedicated to this area and the problem is far from being solved.
Why the need?
It has important advantages over other biometric technologies.
• It is non intrusive and easy to use method.
• It has become one of three identification methods used in e-passports, and a biometric of choice for many other security applications.
• Cognitive and perception models constitute an important platform for inter-disciplinary research, connecting scientists from seemingly incompatible areas and enabling them to exchange methodologies and results on a common problem.
• Used in neuro-biological, psychological, perceptual and cognitive experiments.
• Provide potentially useful insights into how our visual system codes, stores and recognises faces. These insights can then be connected to artificial solutions.
With the growing number of applications in everyday life, image and video-based recognition methods are becoming important research topic. Effects of pose, illumination and expressions are issues currently most studied in face recognition.
After 9/11 tragedy, governments in all over the world started to look more seriously to the levels of security they have at their airports and borders. Therefore, most researchers have concentrated on algorithms of segmentation, feature extraction, and recognition of human faces which are generally realized by face recognition software implemented on standard computers. A face recognition system capable of doing face localization and recognition in real time has many applications in intelligent man-machine interfaces and in other domains such as very low bandwidth video conferencing, and video-email. Thus, these solutions can be the alternative to everyday security solutions that presently exist in many places.
Jacob Michael, the author of this article, has expertise knowledge in using facial recognition software for long years for offering facial recognition services.
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