**3.6. Limitations**

sufficient for biometric identification. For these purposes, it is not necessary to obtain an

In connection with a device from EyeDentify, there were two main representations of the

• The original representation has 40 bytes. This is contrast information encoded by real and

• The new representation has 48 bytes. This does not contain time domain contrast information. The main advantage of time representation is faster and more efficient processing

The retina template contains 96 fields of 4-bit contrast numbers from 96 scans of concentric circles in the time domain, that is, 96 × 4 = 48 bytes. Intensity in the time range can take values

In the retina, when we talk about new research, the situation is relatively simple because the algorithms are searching the image for *bifurcations* and *crossings*, whose positions clearly define the person. The example is shown in **Figure 20**. Recognition becomes problematic when a stronger pathological phenomenon (e.g., a hemorrhage) occurs in the retina that affects the detection

**Figure 20.** Extracted features (bifurcations and crossings, incl. connection of macula and blind spot) in the retina.

imaginary spectrum coordinates generated by Fourier transform.

in the interval <−8.7>, normalizing for this layout—4 bits of intensive layout.

image with too much area and resolution.

with less demanding computing power.

retinal image:

26 Machine Learning and Biometrics

Of popular biometrics, retinal recognition may be the most restrictive. They are not definite, but there is currently no system that can remove these shortcomings to a greater extent [20]:

