Improving fingerprint based gender identification technique using systematic pixel counting

Finger prints are considered as the best tool of identification. Gender identification from fingerprints is an important step in forensic anthropology in order to identify the gender of a criminal and minimize the list of suspect search. Fingerprint identification and classification has been extensively researched in the literature however very few researchers have studied the fingerprint gender classification problem. In the present work, we proposed an easy and efficient technique to classify gender of a person using systematic fingerprint ridge counting to a valley area. The study was carried out on the age group of 18 to 40 years where the students, workers, housewives etc are taken as the subjects. An optimal threshold for each transform is chosen for better results. It is found that the proposed system produces accurate decision of 85% of male and 74% of female. The overall performance of the system is found to be satisfactory and useful to forensic anthropology.