A Review on Cridetinator


  • Bharat Dutt Mathur student
  • Shivam Patel
  • Arpit Agarwal


Machine Learning, Haar-Cascade, Open CV


Cridetinator” was built with an objective to serve the society by creating
awareness about ongoing crimes through an investigation and visualizations about crime from past records. Accordingly, with the assistance of
progressive expertise, various devices are being used/installed for the
security resolve in public as well as private places to provide surveillance system activities. Out of those commonly used is CCTV camera’s,
the footage of which is very helpful to recognize suspects on scene.
This system can sense and diagnose face inevitably as per the criminal
record. In such scenario this system is helpful to successfully enforce
the law or aid any organization to perceive or diagnose the suspect.
As of accuracy, the results show that about 80% of input photo can
be matched with the template data. This system is executed using the
skills available in the Open- Computer-Vision (Open CV) library and
methodology with Python. For face detection, Haar- Cascades and face
detection libraries were used. As per security standards of this system.
Only authorized user can retrieve the essential information, because to
access the information, the administrator ID and password is required

Author Biographies

Bharat Dutt Mathur, student

Department of CSE/IT
Global College of Technology, Jaipur, India

Shivam Patel

Department of CSE/IT
Global College of Technology, Jaipur, India

Arpit Agarwal

Department of CSE/IT
Global College of Technology, Jaipur, India


DOI 10.1007/s00146-014-0539-6 Devendra KumarTayal, Arti Jain, Surbhi Arora, Surbhi Agrawal, Tushar

Gupta, Nikhil Tyagi, Crime detection and criminal

identification in India using Data Mining techniques.

Survey of data mining techniques for crime detection:

Shamaila Qayyum, Hafsa Shareef Dar.

DOI:10.1088/1742-6596/1000/1/012046 S.Prabhakran,

Shilpa Mitra: Survey of analysis of Crime Detection

Techniques using Data Mining and Machine Learing.