A Comparative Study on the Difference of Fingerprint Ridge Density Among Males on their Profession

A specific biometric characteristic that makes it easier to find people is their fingerprints.  For many years, dermatology the inquiry into fingerprints has been a key component of forensic research.  Ridge density, which indicates the number of ridges in one specific area of an individual’s fingerprint, is a notable feature of fingerprints.  Fingerprint ridge density differs by gender, age group, and racial or according to research.  However, literature examining the differences in ridge density amongst guys in various professions is significantly lacking. This knowledge gap is essential because it has a major impact on biometric and forensic investigation. During the growth and development of the fetus, genetic and environmental factors interact to create fingerprints. The complex relationship between these variables causes special patterns and traits of fingerprints, including ridge density. Since the ridge density is a critical side of the fingerprinting. According to research, ridge density Persons should vary in density, individuals and special groups showing high or low densities. The fingerprint of a person is crucial to prove their identification and prove their specialty. These parts are also crucial to the performance of the common crime performance. Analyzing the fingerprint ridge density (FRD) in connection with gender is often measured by the arrival of the unit distance. This analysis is likely to examine the difference in the occupation. This study, fingerprint ridge density, examines the difference between men based on their employment and how different workforces may affect this biological character. As an example, clear workers will end up with ridge patterns, while the office-based or physically demanding roles can help maintain the ridge density. A person's fingerprint ridge density, which is influenced by genetic factors, is the number of ridges in the unit area that remain through their life.  This research aims to examine if there is a significant difference in the fingerprint ridge density among men working in various occupations. This is trying to determine whether employment actions and work conditions will affect dermatoglyphic traits, especially the fingerprint ridge density. Locally and globally, the ridge in the male fingerprinting is crucial to compare the Denzerization of the Denzerus according to their employment. This increases the forensic identification by supporting criminal profiling, elimination, and cool investigations. This helps to create more accurate forensic databases and enhance the validity of the fingerprint evidence in the court. It helps the job testing by identifying identity fraud and employment claims. By increasing cooperate with law enforcement organizations, like Interpol, in the investigation of transnational crimes, it makes cross-border investigations easier on a global basis. Research has broader implications for improving forensic science, law enforcement, and crime-fighting efforts around the world. It also improved the organization of forensic techniques that ensure the similarity in the organicitative analysis procedures across countries, but also by preventing biometric confirmation systems.

METHODS

A total of 200 samples were collected from four different professions: teachers, software employees, drivers, and construction workers. Each profession contributed 50 samples.  After their fingerprints were taken, participants were told to wash their hands accurately.  In order to obtain all 10 rolled fingerprints, individuals were instructed to keep up constant pressure with their fingertips on a black inkless pad before transferring the prints onto paper. The fingerprints are collected with the content of the individuals. The materials employed in this study included a black ink pad, fingerprint slips, a roller, a magnifying glass, a pencil, a measuring scale, and consent forms. A square measuring 5mm by 5mm was drawn on a transparent film and placed over the selected area of the fingerprint samples. The square were drawn and ridges was counted from core to the other end diagonally the while dots were excluded from the count. This count represented the number of ridges within a 25mm² area, reflecting the ridge density. Values were obtained for all ten fingers, and the mean was calculated, providing a single data point for each individual. The overall average was determined using SPSS software. Notably, there is a significant variation in fingerprint ridge density among males based on their occupation.

RESULT

Table 1: Mean distribution of fingerprint ridge count among different professionals

The table presents the mean distribution of fingerprint ridge counts among professionals in four different occupations: teachers, software engineers, drivers, and construction workers. According to the data, teachers have the highest mean ridge count of 12, which indicates that the ridge density was less followed by software engineers with a mean of 11, in this the ridge density was lesser when compared to the teaching profession. Drivers have a mean ridge count of 10, the ridge density was lesser than software engineers while construction workers have the lowest with a mean of 9 so they have lowest ridge density.