GENDER IDENTIFICATION SYSTEM FOR CRIME SCENCE ANALYSIS USING FINGERPRINTS

B, Jaison (2017) GENDER IDENTIFICATION SYSTEM FOR CRIME SCENCE ANALYSIS USING FINGERPRINTS. International Journal of Advances in Signal and Image Sciences, 3 (2). p. 1. ISSN 2457-0370

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Abstract

Gender identification or classification is a challenging task in computer vision as the biometrics of male and female such as fingerprints, face, vein have many variations. Among the various biometrics, fingerprints are commonly available in a crime scene. In this, study, gender identification system for crime scene analysis using fingerprints is presented. Initially, the fingerprints are de-noised by median filter and Otsu thresholding is employed to binarize the fingerprints in the preprocessing stage. Then, the features are extracted by Box-Cox transformation method. Finally, the classification is made by logistic regression classifier. A better classification accuracy of 96% is achieved by the gender identification system using Box-Cox transformation and logistic regression classifier.

Item Type: Article
Subjects: STM Article > Multidisciplinary
Depositing User: Unnamed user with email support@stmarticle.org
Date Deposited: 28 Jan 2023 07:52
Last Modified: 27 Apr 2024 13:20
URI: http://publish.journalgazett.co.in/id/eprint/294

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