The first stage embodies a linear transform of the data, typically in the form of a filterbank, the second stage reduces the dimension of the data through a nonlinear functional, typically in the form of health indicators, and the last stage supplies a statistical decision. Although several ...
A 36-dimensional feature vector is formed with the total energy in each of the filtered images forming a feature. For decision making, two different classifiers are considered—LDC and the commonly used NN classifier. It was observed in several experiments that both the classifiers perform well ...
Both linear and decision feedback structures have been considered. In [2, 4–6], it has been demonstrated that the single-carrier frequency-domain equalization may have a performance advantage and that it is less sensitive to nonlinear distortion and carrier synchro- nization inaccuracies compared ...
The L1-norm is used for feature extraction as it helps in faster computation of features which enables sparsity in the solution. We tested many norm based features such as L1,L2,L3,L4 and L∞-norms as well as a few non-linear features such as fractal dimension, hurt exponent and ...
Next, to obtain more audio details, we propose a feature fusion strategy to extract the MFBSS feature from the background noise. Then, we develop a decision fusion strategy to detect and localize all the possible splicing points. Finally, we evaluate our method against t...
This paper presents a shift, scale, and rotation-in- variant technique for iris feature-representation and fused postclassification at the decision-level to improve the accuracy and speed of the iris-recognition system. Most of the iris-recognition systems are still incapable for providing low ...
We have developed a decision level information fusion framework which improves the fingerprint verification accuracy when multiple matchers, multiple fingers of the user, or multiple impressions of the same finger are combined. A feature verification and purification scheme is proposed to improve the ...