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It is shown that the presented methods yield better results.
All the presented methods have their particular advantages and disadvantages.
The presented methods were checked by the experiment and analytically.
Numerical examples evaluate the presented methods and illustrate their benefits.
The presented methods are evaluated with extensive experiments.
Numerical results show the efficiency of the presented methods.
The presented methods have low computation times; consequently, they can be applied to screen large databases.
The presented methods in [9] have shown their efficiency in predicting the quality of fingerprints images.
Objective and subjective experiments were undertaken to evaluate the presented methods, as summarized in Table 1.
Figure 18 shows the cumulative probability of the error distances for the presented methods.
A further comparison in the numerical aspects demonstrates the effectiveness and accuracy of the presented methods.
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