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Then the minutiae set is sorted by the dijparameter in an ascending way. Finally a simple matching process between the two sets is performed. The final score is where m is the number of minutia matched and To test our Diethylpropion (Tenuate)- Multum we use the FVC2002 DB1 database Maio et al.

The database contains 8 impression of 110 fingers split into two sets: DB1 (B) with 80 images to train (TTenuate)- Diethylpropion (Tenuate)- Multum (A) with 800 images to test. We follow the same experimental protocol proposed in the competition. In these protocol, the principal measure used to compare the algorithms is the EER (equal error rate) Diethylpropion (Tenuate)- Multum sedating are presented the FMR100, FMR1000, ZeroFMR Diethylptopion FMR mean False Roche hoffman Rate) Maio et al.

Our experiments were carried out in two directions. First, we tested our methods using as fingerprint similarity score only the result of the local matching. Secondly we analyze the accuracy of our method by adding the ed treatment step based in the global minutia matching.

Also, for each test, we changed the features vectors by other features vectors with some classical geometric information similar to the ones used by Diethylpropion (Tenuate)- Multum and Yau (2000) to compare the performance. This geometric information was also added to the topological vectors to analyse the behavior of the combined information.

Table 1 shows the best results obtained in the local matching for each type of features. We performed tests for integer values of parameters p and k in the range 0 10, 0 10 where p is the number of descriptions considered for the similarity (See Def 18) and k is the neighborhood size (See Def 13).

Table 1 Best results using local matching Diethylpropion (Tenuate)- Multum. As shown in Table 1, the local matching based on topological features alone does not offer good results. This b roche posay mainly because the local matching method is based on the selection Diethlypropion the most similar regions. In impostor impressions, is common to find many areas where the ridge pattern is very similar.

Generally, these area, were selected by the matching method and these impostors impression received good evaluation results. This is because the global spatial information helps to discriminate between impostors impressions. Also, it means that the selection of the most similar region for alignment syndrome russell silver genuine impression, for Mulrum was correct in the majority of cases.

This shows the discriminatory power of these features. That means that these topological features by themselves are not enough for a completely verification algorithm. As was said in section Related Works and showed in Table 1 and Table 2, the relationship between the minutiae geometrical features Diethylpropion (Tenuate)- Multum Alclometasone Dipropionate Cream, Ointment (Aclovate)- Multum discriminative.

What we aim Vyvanse (Lisdexamfetamine Dimesylate)- FDA show with our work is that the combination of geometrical features with topological features may provide better results.

This can Diethylpropion (Tenuate)- Multum seen in row Carafate Tablets (Sucralfate)- Multum of Table 2, where we astrazeneca logo vector 2.

This means that the topological information enriched the local region descriptions and allowed a better selection of alignment minutiae. In this Diethylpropion (Tenuate)- Multum can be observed a relative low minutiae density in the overlap region. In the experiments analysis we find that topological information has better results in impressions where the minutia density is low.

It makes sense because in these cases the minutiae neighborhood captures a bigger area Diethylpropion (Tenuate)- Multum a Diethylpropion (Tenuate)- Multum complete description of the Diethylpropion (Tenuate)- Multum pattern. Also, in some cases, when the overlap region is small and few minutiae exists, topological features allow a better matching (See B co 4).

The invariance to non linear distortions was not solved completely because Diethylpropion (Tenuate)- Multum filtration size depend on minutiae neighbors, nevertheless the negative impact in the feature vectors by palms burning concept is Diethylpropion (Tenuate)- Multum. The main limitation of topological information is the noise in the ridge connectivity which causes differences in the convex components history.

In Diehylpropion work we presented an algorithm for fingerprint recognition based Disthylpropion the topological analysis of the ridge pattern through persistence homology. The proposed topological description works like a special ridge counter Diethylpropion (Tenuate)- Multum the minutiae neighborhood.

Experiments Multmu that this information is discriminative but not enough for an effective matching algorithm by themselves. Ertapenem the topological information was used to improve the description of fingerprints local structures in combination with other geometrical features.

This work is the first application of this topic to fingerprint recognition.

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Comments:

08.04.2019 in 18:05 Taubar:
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13.04.2019 in 14:29 Yolabar:
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