Fujitsu delivers cashless, contactless retail experience for masked shoppers
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Fujitsu Laboratories Ltd has announced the development of a new multi-factor biometric authentication technology to deliver an innovative shopping experience, combining non-contact biometrics that filter the verification target through facial data with identification performed via palm vein recognition. This technology enables identification with greater than 99% accuracy even when the user wears a mask, and will be showcased at a concept cashless Lawson convenience store at the Fujitsu Technology Square office in Shin-Kawasaki for a field trial.
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Users wearing masks present challenges to conventional facial recognition filtering technologies because a large part of the face is obscured, rendering authentication impossible in some cases. With the newly developed technology, however, differences in the appearance depending on the presence or absence of the mask can be absorbed by generating a composite image that combines the mask with the face image and training the model, achieving filtering accuracy of greater than 99%, or equivalent to that without a mask.
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Fujitsu has additionally enhanced its existing palm vein authentication sensor technology by improving the user interface so that users know how close to position their hand from the sensor for smooth authentication. This technology was ranked 6th amongst 147 participating global vendors and 1st place among Japanese vendors in the face authentication vendor test conducted by the United States’ National Institute of Standards and Technology (NIST).
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The features of the developed technology are as follows.
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With typical facial recognition technology, when a user is wearing a mask only the exposed eye area is checked in order to extract features such as the shape and position of the face. While this method can help reduce the influence of wearing a mask over an accurate reading, it cannot extract the features of the entire face, presenting the possibility that the target user cannot be recognized due to insufficient data.
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In order to reduce this effect, the newly developed technology generates an image of the user’s face without a mask while taking into account the extraction of features of the entire face, like its shape and contours. This means that even when the user is wearing a mask, the user can be recognized against the corresponding facial image can be narrowed down from a large database with the same level of accuracy as without a mask. Specifically, the technology estimates the position of the face based on facial features such as the position of the eyes and nose, and based on the estimation results, an artificial mask is resized and reshaped then superimposed over the face image to generate a natural masked facial image. In addition, the system uses various types of masks in order to deal with situations in which masks of various colors, patterns and shapes are worn by users . This makes multi-factor authentication more hygienic and easier to use by allowing people to undergo authentication without removing their mask.
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The user interface of the palm vein authentication system has also been improved to enable smoother use. A palm-shaped light has been added to the sensor, and the color and the pattern of the light changes according to the distance of the hand, so that the appropriate height for accurate authentication is apparent. This allows people who are not familiar with palm vein authentication to adjust their palms to the appropriate height for smooth, contactless authentication.
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