This document describes a proposed prisoner face detection system with 4 group members and a faculty guide. It discusses the existing manual criminal identification system and its limitations. The proposed system would use face detection and image slicing to allow eyewitnesses to identify criminals by facial features stored in a database. It provides advantages like being less complex and requiring no direct contact. The system design involves administrators adding criminal data and images and operators retrieving images for eyewitnesses.

2. PRISONER FACE DETECTION SYSTEM
GROUP MEMBERS
 FARHAN NAIK.
 KANCHAN VAVA.
 SHWETA FULWANI.
 AKSHAY AUTI.
UNDER THE GUIDANCE OF
Miss. Suwarna Nimkarde.

3. POINTS TO DISCUSS
 Existing System
 Limitations of Existing System
 Proposed System
Working
 Flow of System
 Advantages of Proposed System
 Application
 Soft. & Hardware Specification
System Design
conclusion
 References

4. EXISTING SYSTEM
In existing system criminal information is stored in
file format with outdated images and low quality
images.
Using this information it is not possible for eye
witness to guess the criminal, so there is need to
develop a better method for identifying criminals like
finger print, DNA…Etc.
Among all these methods face detection method is
cost effective and more accurate.

5. LIMITATIONS OF EXISTING
SYSTEM
Using Existing System Its Difficult for eye
witness to guess the criminal .
It’s Difficult ToMaintain Data Physically.
Human Interaction Required.

6. PROPOSED SYSTEM
 Prisoner face detecting system can be used in police
department.
 This software contains front end and back end applications
where front end is used to visualize the output and back
end is used to store data.
 Initially criminal images are stored in database along with
his bio data. Every image is sliced by eyes, hair, lips and
nose..etc and stored in database as separate record.
 These images are shown to eye witness while investigation
separately, if witness can judge any part of criminal we can
recover entire criminal record based on that clue.
 With this system police will provide better option to
witness to judge criminal.

7. WORKING
Capture Image
Convert To Gray Image
Edge Detection
Comparison
Report The Admin

8. FLOW OF SYSTEM

9. ADVANTAGES
OF PROPOSED SYSTEM
 Unlike many other identification methods (e.g., fingerprints,
voiceprint, signature), they do not need to make direct contact
with an individual in order to verify their identity
 Less Complex Than OtherMethod.

10. APPLICATION
IN MANY SERCURITY SYSTEM
It can be used in VIDEO SURVEILENCE SYSTEM
It can be used in CCTV(CLOSED CIRCUIT
TELEVISION)
It can be used in Criminal Investigations, Home
Security, Military, Intelligence

11. REQUIREMENT SPECIFICATION
SOFTWARE
SPECIFICATIO
N
• Operating System
Windows XP
• Programming
language :
• JAVA
SOFTWARE
TOOLS
• Backend
• MS Access
HARDWARE
SPECIFICATION
• PROCESSOR: Speed
minimum: PIII 800 MHz
• RAM: Minimum: 128 MB, 256
MB

12. SYSTEM DESIGN
E-RDIAGRAMS BETWEEN ADMINISTRATOR
AND EMPLOYEE:
User id
Pwd User id
Pwd
Administrator Authentication Employee

13. E-R DIAGRAMS BETWEEN EMPLOYEE AND
EYEWITNESS:
Employee Viewing &
selecting,
images
Eyewitness
User
id
Pwd
User
id Pwd
Criminal
details
Criminal
images
Criminal
images

14. E-R DIAGRAM BETWEEN EYEWITNESS AND
ADMINISTTRATOR
Administrator
Authen
tication Eyewitness
User id
Pwd
User id Pwd

15. USE CASE DIAGRAM
Administrator:
Login
Inserting/Updating Criminal Details
Splitting/Updating Images
Inserting/Updating Face Details
Already Existed Criminal
New Criminal
Deleting Images
Administrator
criminal

16. Client (Operator):
operator Login
retriving the images
operator Criminal
identifying the images

17. ACTIVITY DIAGRAM
Administrator:
Administrator
check
yes
No
Criminal Details Operations
Insert Update Delete View splitting Merging

18. Operator:
Operator
check
yes
No
Retrieve Image
Identify Image

19. CONCLUSION
This system seems to be working fine and
successfully. This system can able to provide the
proper training set of data and test input for
recognition. The face matched or not is given in
the form of picture image if matched and text
message in case of any difference.

20. REFERENCES
WEB REFERENCES
• http://www.filestub.com
• http://www.ebookee.org
• http://www.google.com