Fingerprint Based Gender Identification Using Digital Image Processing and Artificial Neural Network

Abstract

Every person has a unique fingerprint which can be used for identification. Fingerprints are widely used for forensic cases in criminal investigations. It would be useful to be able to distinguish fingerprints samples based on gender to reduce number of persons of interest in a criminal investigation. This paper discusses a system implemented for identification of gender based on fingerprints. Digital Image Processing and Artificial Neural Network (ANN) techniques were used to implement the gender identification system. Various preprocessing techniques such as cropping, resizing and thresholding were carried out on each image. Feature extraction was carried on each pre-processed image using Discrete Wavelet Transform (DWT) at 6 levels of decomposition. The extracted features were used for implementing ANN based on Back Propagation algorithm. Fingerprint images were sourced from publicly available online datasets. A data set of 200 images of left thumbprint, which included 100 male and female fingerprint images. A training set of 100 images was used for testing purpose, which included 50 male and female images respectively. The accuracy achieved for identifying fingerprints was found to be 78% and 82% for male and female samples respectively.