**5.2 Frequency of features occurrences**

**Figure 7** shows the frequencies for manual marking by SW1. The program SW4 also shows the outer circle area in which at least some points occur, and the axes of the retina and the inner ellipses indicate areas with minimal occurrences of points around the yellow (yellow) and blind (black) spots.

#### **Figure 6.**

*Comparison of manual and automatic marking. Manually marked points are displayed by green points and automatically marked points are displayed by blue points.*

#### **Figure 7.**

*Frequency visualization of bifurcations and crossings.*

For SW5, we randomly selected 10 persons from database EBD. Each have three images for the left and right eye which are marked e.g. 1002-2-R for person 1002's second image of the right eye. We mark all retinas by SW1 very carefully. The first and third images of the eye were marked by a specialist such that at least 24 hours must have passed in between the marking of the retinas for the same person. The second images were marked by an ordinary computer user who is not involved in the project.

**91**

one person.

*Retina Recognition Using Crossings and Bifurcations DOI: http://dx.doi.org/10.5772/intechopen.96142*

**Figure 8** shows two images of the same retina that are taken at significantly different angles. After the marking by SW1 and determining the similarity of the

compare with second eye of same person 65.52% 39.69% 80.38% compare with different person eye 67.66% 45.32% 74.21% compare with our school database (different persons) 57,62% 43,36% 74,58%

same eye, marked by different person 86.51% 78.90% 93.16% same eye, marked by same person 93.54% 88.54% 95.78%

**Avg value Min value Max value**

**Avg value Min value Max value**

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

retinas by SW5, the result was 91,09%.

*Sample of two images of the same retina in the EBD database.*

**6. Conclusions**

**Figure 8.**

**Table 1.**

**Table 2.** *Verification results.*

*Recognition comparing results.*

**Tables 1** and **2** shows the average results of evaluation after SW5.


#### **Table 1.**

*Applications of Pattern Recognition*

*automatically marked points are displayed by blue points.*

*Frequency visualization of bifurcations and crossings.*

**Figure 6.**

**90**

**Figure 7.**

For SW5, we randomly selected 10 persons from database EBD. Each have three images for the left and right eye which are marked e.g. 1002-2-R for person 1002's second image of the right eye. We mark all retinas by SW1 very carefully. The first and third images of the eye were marked by a specialist such that at least 24 hours must have passed in between the marking of the retinas for the same person. The second images were marked by an ordinary computer user who is not involved in the project.

*Comparison of manual and automatic marking. Manually marked points are displayed by green points and* 

**Tables 1** and **2** shows the average results of evaluation after SW5.

*Recognition comparing results.*


#### **Table 2.**

*Verification results.*

**Figure 8.** *Sample of two images of the same retina in the EBD database.*

**Figure 8** shows two images of the same retina that are taken at significantly different angles. After the marking by SW1 and determining the similarity of the retinas by SW5, the result was 91,09%.
