In this section, the proposed template selection is compared to MDIST [10] template selection.
While, template selection is an effective method to reduce the number of fingerprint templates in database.
The rule of thumb for template selection is to favor the proteins whose sequences align better with the targets in the important regions, such as the adenosine-5'-triphosphate (ATP -binding pocket in kinATP -bindingnsmembrane domains in G pocketn-coupled receptors (GPCRs).
What contributes to the template selection is not clear.
In individuals with hippocampal pathology, template selection is critical (Avants et al., 2010).
However, alignment errors and template selection are still the main bottleneck for current template-base modeling methods, especially when proteins under consideration are distantly related.
Since template selection is an important factor that affects quality, therefore, an attempt was made for a suitable template searching using mGenTHREADER [ 14], which is an online tool for searching similar sequences, based on sequence and structure-wise similarity.
The main contributions of this article to the fingerprint verification are (1) a template selection method is proposed, and this method is more robust and effective than the MDIST.
First, in the enrollment stage, some fingerprint images of the same finger are enrolled, and a template selection method is used to choose some fingerprints which are the best represent of this finger as the templates.
In Table 2, we show how the threshold value t of Equation 19 for removing the GMM outliers affected the recognition performance, where the template selection method was MLTS with the KL distance, and 20% template representatives were selected.
