Conference Paper

Fingerprint-Based Gender Classification.

Conference: Proceedings of the 2006 International Conference on Image Processing, Computer Vision, & Pattern Recognition, Las Vegas, Nevada, USA, June 26-29, 2006, Volume 1
Source: DBLP

ABSTRACT Gender classification from fingerprints is an important step in forensic anthropology in order to identify the gender of a criminal and minimize the list of suspects search. A dataset of 10-fingerprint images for 2200 persons of different ages and gender (1100 males and 1100 females) was analyzed. Features extracted were; ridge count, ridge thickness to valley thickness ratio (RTVTR), white lines count, ridge count asymmetry, and pattern type concordance. Fuzzy C- Means (FCM), Linear Discriminant Analysis (LDA), and Neural Network (NN) were used for the classification using the most dominant features. We obtained results of 80.39%, 86.5%, and 88.5% using FCM, LDA, and NN, respectively. Results of this analysis make this method a prime candidate to utilize in forensic anthropology for gender classification in order to minimize the suspects search list by getting a likelihood value for the criminal gender.

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    ABSTRACT: Although several studies have recently assessed sex differences in fingerprint ridge density and its variability in human populations from different origins, such a study has not been carried out yet in the Amerindian population. The goal of this study was to determine the topological and sexual differences in fingerprint ridge density (RD) in native subjects from two samples of northwestern Argentina (Jujuy province) living at different altitudes. The results were compared with those obtained from a Spanish population sample. The study was based on data from all 10 fingerprints of 393 adult Argentinian men and women, 193 from the Puna-Quebrada region (more than 2500 m above sea level) and 200 from Ramal (500 m above sea level). Ridge density was assessed for three different areas (radial, ulnar and proximal) for all 10 fingers of each subject. In both samples, significant differences between areas were obtained, so radial RD > ulnar RD > proximal RD. No significant differences were found between samples in males, while females from both samples significantly differed in the radial and proximal areas. Females have higher RD, so narrower ridges, than men, in all areas and all fingers. Application of Bayes' theorem allowed us to obtain a ridge density threshold for discrimination of sexes in Argentinian samples and the threshold for discrimination of populations between Argentinian and Spanish samples. These results can be useful for forensic use.
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May 22, 2014