Development of a fingerprint gender classification algorithm using fingerprint global features

• Main Authors: Abdullah, Siti Fairuz, Abdul Rahman, Ahmad Fadzli Nizam, Abal Abas, Zuraida, Mohd Saad, Wira Hidayat
• Format: Article
• Language: English
• Published: Science and Information Organization 2016
• Online Access: http://eprints.utem.edu.my/id/eprint/26800/2/PAPER_35-DEVELOPMENT_OF_A_FINGERPRINT_GENDER_CLASSIFICATION_ALGORITHM.PDF; http://eprints.utem.edu.my/id/eprint/26800/; https://thesai.org/Downloads/Volume7No6/Paper_35-Development_of_a_Fingerprint_Gender_Classification_Algorithm.pdf

In forensic world, the process of identifying and calculating the fingerprint features is complex and take time when it is done manually using fingerprint laboratories magnifying glass. This study is meant to enhance the forensic manual method by proposing a new algorithm for fingerprint global feature extraction for gender classification. The result shows that the new algorithm gives higher acceptable readings which is above 70% of classification rate when it is compared to the manual method. This algorithm is highly recommended in extracting a fingerprint global feature for gender classification process.