The aim of the paper “Face Recognition Technology” is to analyze the Face Recognition technology in today’s world of network, which is getting increasing importance due to the growing security risks and industrialization of hackers…
Availability of ‘biometrics’ technology provides controls for verifying true identity of an individual. These controls are automated processes that recognize physiological characteristics such as fingerprints, face, eyes, DNA etc. of a living person which are not easy to forge as they are attributes of an individual gifted by nature. There are also automated processes that recognize individual behaviors such as handwriting style, key stroke patterns etc. (Lin, 2000)
Physiological controls are more stable when compared with behavioral controls. The main reason is that the features of physiological controls are non-alterable unless some serious injury is inflicted on a living being. On the other hand the patterns of behavior controls fluctuate with the mood and activities of an individual. In real-life, it is found that verification of physiological attributes is although very accurate, yet it is far more intrusive than the behavior attributes (Lin, 2000)
One of the few biometrics controls that have the merits of both low intrusiveness and high accuracy is the Face Recognition technology. Researches in the field of image processing, security and psychology were attracted towards the concepts of computer vision which led to the designing of face recognition technology. (Lin, 2000)
The real-world image has only size in inches or centimeters. The capturing device such as camera or scanners uses digitization process through which it stores the number of pixels that contains in an image. It is called Resolution which is of two types; Spatial Resolution and Colour Resolution (JISC Digital Media, 2006)
The capturing device in Spatial Resolution is concerned with the frequency at which samples are taken from the real-world object or art-work. Frequency is mostly expressed as samples per inch (spi) when scanning and pixels per inch (ppi) when processing the digital image. The resolution to use for capturing an image is dependent mostly on its ‘end-use’. ...
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(Face Recognition Technology Research Paper Example | Topics and Well Written Essays - 1000 Words)
“Face Recognition Technology Research Paper Example | Topics and Well Written Essays - 1000 Words”, n.d. https://studentshare.net/information-technology/469505-face-recognition.
The author has rightly presented that global processing is basically about processing an image holistically. It is dominated by global precedence with an individual identifying features based on global, not local, elements. In general, global precedence is used over local parameters, however, for certain individuals, they may be more inclined to consider local features.
Given the value of being able to recognize faces, both at the individual level, and at the social level; research in cognitive sciences has helped in understanding the principles that affect this process and the problems and errors that are likely to be committed.
Of all these biometrics, it is facial recognition which is being met with contrasting views and arguments regarding questions of its use, accuracy and usefulness; and since it relates to visual recognition and identification, it offers concrete physical identification, that its use has given rise to concerns of invasion of privacy.
However these technological advancements have come with some challenges and threats which if not properly addressed may negate the gains that have been made, therefore in this essay I will look at the challenges and the threats that we face in the use of technology in our interactions.
It is questionable whether participants in facial recognition tasks decide based on these facts or due to other influential factors such as the orientation of images upon presentation, either the images are upright or inverted. This study was carried out to identify whether the orientation of images upon presentation has a significant effect on the decisions made participants of the facial likeness task.
The first group of White individuals was subjected to the recognition test. Each took the turn of recognizing which two pictures (1 white face and 1 black face) belong to one person. The speed of recognition was recorded accordingly in terms of time in minutes.
And despite any fancy slide or computer show you might use, your most effective selling tool will be your verbal presentation and interaction with the prospective buyer (Stone, 1997). In almost every case, the owner of a small business will be able to make the most effective sales presentation, even more so than someone with more extensive sales experience.
If unsure whether an image is a face or not, transform it to face space, then do the inverse transform to get a new image back (Danner, T. & Datta, Indraneel, "Eigenfaces Group - Algorithmics", par. 7).
After scrutinizing the images, we can observe some similar features of the eigenface from the three original images (Amber1, Andy2, and Jimmy3).
Face recognition is chiefly used in forensic science. The technicalities in recognition process are the ongoing research modalities. The use of face recognition in judiciary involves both the identification part of the process and the confidence part of the eye witness.