**6. Conclusions**

In this paper, we have presented different approaches for the evaluation of individual parameters in human recognition based on the retina of the human eye. The main principle was to locate the individual bifurcations and crossings in the retinal image. The main part was, of course, based on a comparison of the locations of the points in both images. Another part of the principle was based on a set of almost 1000 manually marked images where all bifurcations and crossings were located. Were tested these points in images for placement accuracy by automatic search. Depending on the frequency of occurrence of points in different parts of the retina, these points had different weights for final correspondence. Finally, the procedure was tested on several differently photographed retinas of one person.

In our principle, it is not a matter of finding the best recognition algorithm but finding out the best properties of the individual parts of the procedure. The algorithms could be improved especially in the recognition part itself. The evaluation algorithm was illustrative only to show how the individual parts worked.
