## 2 State of the Art  
### Fingerprint Acquisition  
Fingerprints are the most widely used modality for biometric recognition [5]. Scars, cuts, or other significant types of damage to the fingers can be caused by the person's age or profession. These states can seriously affect the raw biometric image quality, and consequently lower the performance of the biometric system based on the fingerprint modality. There is a possibility that fingerprint recognition process can result in a low accuracy. The reason for such behavior is in most cases bad image accuracy. Bad image accuracy can be caused by the acquisition environment or by the state of the finger skin. It is possible to have blisters, cuts or wrinkles on the fingerprint area. Fingerprint skin can be coarse, too dry, or too wet. All these states affect recognition accuracy. Also, human behavior has a significant impact on the fingerprint acquisition process. Human-computer interaction deals with these behavioral aspects of fingerprint acquisition [6]. For example, the user of a fingerprint biometric system can press the sensor too strong or too weak. Fingers can be improperly aligned to working area of the fingerprint sensor. The duration of finger contact with the acquisition sensor may be too short. Authors from China [7] have also analyzed the impact of the image quality on the fingerprint recognition precision. Experiment participants belonged to the population aged between 21 and 25 years. Acquisition was performed from December 2013 to May 2017, and data was collected from 1000 participants per month. Seasonal factors were monitored as well as their impact on fingerprint image quality, ESR (Enrollment Success Rate) and CPR (Capture Success Rate). Some of the conclusions were that ESR and CPR have the same variations trends and that the image quality varies between different seasons. Better image quality was obtained in the summer, during July and August, than in the winter months. The environmental condition of the acquisition environment, such as the dirty fingerprint sensor area, extremely high temperatures, or unusual lightning can affect fingerprint image quality. Some of the more common conditions which were tested in the controlled environment are cold finger, cold-wet finger, heated finger, soaked finger, glued finger, and dirty finger [8]. The experiment [8] was conducted on four different fingerprint readers. There were 80 participants aged between 21 and 66 years old. Testing was performed in twenty acquisition cycles under controlled conditions. The experiment results have shown that the average value of the FRR (false rejection rate) is in practice greater than the one quoted by the fingerprint sensors manufacturers. The fact that quality of the fingerprint impacts biometric system performance was recognized by [PERSON] et al. [9]. In their research, the authors collected database of 6600 fingerprints collected from 33 persons, by the use of five different optical fingerprint sensors. Different skin states were simulated, such as wet, wrinkled, and dry. The authors have concluded that both the choice of sensors and the skin state affect system performance. In their experiment, [PERSON] and [PERSON] have studied two groups of examinees. The first group had 79 experiment participants, aged between 18 and 25 years. The second group consisted of 62 participants, whose age was over 62 years. The results have shown that the participant age has a significant impact on fingerprint image quality. Authors have used the NFIQ (Nist Fingerprint Image Quality) [10] tool to assess the quality of the fingerprint images. The reason is the large number of low-quality images collected from the group of older participants. The reliable detection of minutiae is very hard in the case of low-quality images. This fact has a direct impact on biometric system precision [11; 12]. The younger population had more high-quality fingerprint images, which resulted in greater system precision.