AI-Based Criminal Identification System A Breakthrough Approach

Year : 2024 | Volume :02 | Issue : 01 | Page : 1-15
By

K. Amrutha Kumari

L. Pratibha

S. Maharshi

D. Avinash Sai

M. Dinesh

  1. Student Department of Computer Science and Engineering, Gayatri Vidya Parishad College for Degree and PG Courses (A), Visakhapatnam Andhra Pradesh India
  2. Assistant Professor Department of Computer Science and Engineering, Gayatri Vidya Parishad College for Degree and PG Courses (A), Visakhapatnam Andhra Pradesh India
  3. Student Department of Computer Science and Engineering, Gayatri Vidya Parishad College for Degree and PG Courses (A), Visakhapatnam Andhra Pradesh India
  4. Student Department of Computer Science and Engineering, Gayatri Vidya Parishad College for Degree and PG Courses (A), Visakhapatnam Andhra Pradesh India
  5. Student Department of Computer Science and Engineering, Gayatri Vidya Parishad College for Degree and PG Courses (A), Visakhapatnam Andhra Pradesh India

Abstract

Identifying and locating a perpetrator is a time-consuming and difficult process. The perpetrators are growing more skilled, leaving no biological evidence or fingerprint impressions at the crime scene. Using cutting-edge face recognition technology is a quick and easy solution. Through the use of linear programming, this research presents an innovative approach to classifying all face tracks collectively. In addition to the following, it incorporates: a novel method for extracting more informative data from aligned transcripts; a particular model for classifying background characters according to their face tracks; the implementation of new HOG (Histogram Oriented Gradients) face features; and a novel approach for labelling all face tracks simultaneously. The conventional systems implemented the CNN classification model for face detection, but due to the time-consuming process to detect face features, we are implementing the HOG algorithm to detect face features from Perpetrator Identification. Moreover, the SVM classifiers were used in the existing system for face recognition which is not detected effectively, therefore we are implementing the KNN classifier to recognize the faces effectively for the perpetrator identification.

Keywords: Face Detection, Face Recognition, HOG Algorithm, KNN, SVM.

[This article belongs to International Journal of Mechanical Dynamics and Systems Analysis(ijmdsa)]

How to cite this article: K. Amrutha Kumari, L. Pratibha, S. Maharshi, D. Avinash Sai, M. Dinesh. AI-Based Criminal Identification System A Breakthrough Approach. International Journal of Mechanical Dynamics and Systems Analysis. 2024; 02(01):1-15.
How to cite this URL: K. Amrutha Kumari, L. Pratibha, S. Maharshi, D. Avinash Sai, M. Dinesh. AI-Based Criminal Identification System A Breakthrough Approach. International Journal of Mechanical Dynamics and Systems Analysis. 2024; 02(01):1-15. Available from: https://journals.stmjournals.com/ijmdsa/article=2024/view=0

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Regular Issue Subscription Review Article
Volume 02
Issue 01
Received May 22, 2024
Accepted June 5, 2024
Published July 11, 2024
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