Crime Prediction for Forensic Analysis-fingerprint Recognition System

Fingerprint recognition has been a cornerstone in forensic science for over a century. Its unique capability to identify individuals based on their unique fingerprint patterns makes it invaluable in criminal investigations. This project comes under Artificial Intelligence where we use deep learning algorithm called convolutional neural networks (CNN)and Keras, Open CV. CNN is mainly used for image recognition and training due to its ability to recognise patterns in images. The existing methods of this project are Live fingerprint scanning, Forensic fingerprint database, Automated fingerprint analysis, etc. Drawbacks of existing methods are human error, false matches, Quality of prints, latent prints, etc. Proposed methods that are developed by this project: Deep learning Based system, Cloud used to store the data. By the given proposed methods we can improve the accuracy rate, data security with the help of cloud.

Publication Details

Journal
International Journal For Multidisciplinary Research
Published
2024-11-22
DOI
https://doi.org/10.36948/ijfmr.2024.v06i06.31360
Primary Topic
Diverse Scientific and Economic Studies
Type
article
Field-Weighted Citation Impact
0.00
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article

Crime Prediction for Forensic Analysis-fingerprint Recognition System

International Journal For Multidisciplinary Research
Diverse Scientific and Economic Studies
article

Crime Prediction for Forensic Analysis-fingerprint Recognition System

article en

Abstract

Fingerprint recognition has been a cornerstone in forensic science for over a century. Its unique capability to identify individuals based on their unique fingerprint patterns makes it invaluable in criminal investigations. This project comes under Artificial Intelligence where we use deep learning algorithm called convolutional neural networks (CNN)and Keras, Open CV. CNN is mainly used for image recognition and training due to its ability to recognise patterns in images. The existing methods of this project are Live fingerprint scanning, Forensic fingerprint database, Automated fingerprint analysis, etc. Drawbacks of existing methods are human error, false matches, Quality of prints, latent prints, etc. Proposed methods that are developed by this project: Deep learning Based system, Cloud used to store the data. By the given proposed methods we can improve the accuracy rate, data security with the help of cloud.

International Journal For Multidisciplinary ResearchVol. 6(6)
Peace, Justice and strong institutions
Openalex Percentile: Top 27%
Diverse Scientific and Economic Studies
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