GENDER IDENTIFICATION SYSTEM FOR CRIME SCENCE ANALYSIS USING FINGERPRINTS
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 syste...
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| Format: | Article |
| Language: | English |
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XLESCIENCE
2017-12-01
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| Series: | International Journal of Advances in Signal and Image Sciences |
| Subjects: | |
| Online Access: | https://xlescience.org/index.php/IJASIS/article/view/23 |
| _version_ | 1817986926610743296 |
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| author | Jaison B |
| author_facet | Jaison B |
| author_sort | Jaison B |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-14T00:14:34Z |
| format | Article |
| id | doaj.art-d5bc0ef8980b4e4794390a2f76e92a08 |
| institution | Directory Open Access Journal |
| issn | 2457-0370 |
| language | English |
| last_indexed | 2024-04-14T00:14:34Z |
| publishDate | 2017-12-01 |
| publisher | XLESCIENCE |
| record_format | Article |
| series | International Journal of Advances in Signal and Image Sciences |
| spelling | doaj.art-d5bc0ef8980b4e4794390a2f76e92a082022-12-22T02:23:10ZengXLESCIENCEInternational Journal of Advances in Signal and Image Sciences2457-03702017-12-01321710.29284/ijasis.3.2.2017.1-723GENDER IDENTIFICATION SYSTEM FOR CRIME SCENCE ANALYSIS USING FINGERPRINTSJaison BGender 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.https://xlescience.org/index.php/IJASIS/article/view/23fingerprints, gender identification, box-cox transformation, logistic regression classifier |
| spellingShingle | Jaison B GENDER IDENTIFICATION SYSTEM FOR CRIME SCENCE ANALYSIS USING FINGERPRINTS International Journal of Advances in Signal and Image Sciences fingerprints, gender identification, box-cox transformation, logistic regression classifier |
| title | GENDER IDENTIFICATION SYSTEM FOR CRIME SCENCE ANALYSIS USING FINGERPRINTS |
| title_full | GENDER IDENTIFICATION SYSTEM FOR CRIME SCENCE ANALYSIS USING FINGERPRINTS |
| title_fullStr | GENDER IDENTIFICATION SYSTEM FOR CRIME SCENCE ANALYSIS USING FINGERPRINTS |
| title_full_unstemmed | GENDER IDENTIFICATION SYSTEM FOR CRIME SCENCE ANALYSIS USING FINGERPRINTS |
| title_short | GENDER IDENTIFICATION SYSTEM FOR CRIME SCENCE ANALYSIS USING FINGERPRINTS |
| title_sort | gender identification system for crime scence analysis using fingerprints |
| topic | fingerprints, gender identification, box-cox transformation, logistic regression classifier |
| url | https://xlescience.org/index.php/IJASIS/article/view/23 |
| work_keys_str_mv | AT jaisonb genderidentificationsystemforcrimescenceanalysisusingfingerprints |