110,067 research outputs found
Symbolic calculus on the time-frequency half-plane
The study concerns a special symbolic calculus of interest for signal
analysis. This calculus associates functions on the time-frequency half-plane
f>0 with linear operators defined on the positive-frequency signals. Full
attention is given to its construction which is entirely based on the study of
the affine group in a simple and direct way. The correspondence rule is
detailed and the associated Wigner function is given. Formulas expressing the
basic operation (star-bracket) of the Lie algebra of symbols, which is
isomorphic to that of the operators, are obtained. In addition, it is shown
that the resulting calculus is covariant under a three-parameter group which
contains the affine group as subgroup. This observation is the starting point
of an investigation leading to a whole class of symbolic calculi which can be
considered as modifications of the original one.Comment: 25 pages, Latex, minor changes and more references; to be published
in the "Journal of Mathematical Physics" (special issue on "Wavelet and
Time-Frequency Analysis"
Optical Font Recognition in Smartphone-Captured Images, and its Applicability for ID Forgery Detection
In this paper, we consider the problem of detecting counterfeit identity
documents in images captured with smartphones. As the number of documents
contain special fonts, we study the applicability of convolutional neural
networks (CNNs) for detection of the conformance of the fonts used with the
ones, corresponding to the government standards. Here, we use multi-task
learning to differentiate samples by both fonts and characters and compare the
resulting classifier with its analogue trained for binary font classification.
We train neural networks for authenticity estimation of the fonts used in
machine-readable zones and ID numbers of the Russian national passport and test
them on samples of individual characters acquired from 3238 images of the
Russian national passport. Our results show that the usage of multi-task
learning increases sensitivity and specificity of the classifier. Moreover, the
resulting CNNs demonstrate high generalization ability as they correctly
classify fonts which were not present in the training set. We conclude that the
proposed method is sufficient for authentication of the fonts and can be used
as a part of the forgery detection system for images acquired with a smartphone
camera
Focus in Ewe
International audience—In this paper, a strides detection algorithm is proposed using inertial sensors worn on the ankle. This innovative approach based on geometric patterns can detect both normal walking strides and atypical strides such as small steps, side steps and backward walking that existing methods struggle to detect. It is also robust in critical situations, when for example the wearer is sitting and moving the ankle, while most algorithms in the literature would wrongly detect strides
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