Project Face Detection

3,334 views
2,991 views

Published on

1 Comment
1 Like
Statistics
Notes
  • Thnx for providing the required slides
       Reply 
    Are you sure you want to  Yes  No
    Your message goes here
No Downloads
Views
Total views
3,334
On SlideShare
0
From Embeds
0
Number of Embeds
1
Actions
Shares
0
Downloads
111
Comments
1
Likes
1
Embeds 0
No embeds

No notes for slide

Project Face Detection

  1. 1. CSE 2100Software Development Project 1 Project Title Face Detection
  2. 2. Supervisor Mr. Md. Aminul Haque Akhand Assistant ProfessorDepartment of Computer Science and Engineering Khulna University of Engineering and Technology Credit: Abu Saleh Md. Musa (0907013) Sanjoy Dutta (0907008)
  3. 3. Objectives• The objective of our project is to design software that can detect human faces from an image.
  4. 4. What is Face Detection• Face detection is a computer technology that determines the locations and sizes of human faces in arbitrary (digital) images. It detects facial features and ignores anything else, such as buildings, trees and bodies.
  5. 5. Why we chose Face Detection Project?• Compatible with Modern Era.• Not common in JAVA.• Basic programme for Recognition(Recognition is not possible without Detection).• Security Maintenance and Media Empowering.• Needed for visual applications in Robotics.
  6. 6. Examples of Implementation 1 Picasa Photo Viewer (people panel)
  7. 7. Examples of Implementation 2• Facebook Tagging
  8. 8. Procedure at a Glance• Read an image from disk (.JPG, etc.)• Convert it into a jjil.core.Image• Generally we’ll have an RGB image (colored image) and so need to convert it to 8-bit grayscale, which is what the Gray8DetectHaarMultiScale class requires.• Load facial properties to the class form Haar profile for detecting faces.• Apply Gray8DetectHaarMultiScale to our 8-bit grey image.• Retrieve result from Gray8DetectHaarMultiScale.
  9. 9. Step by Step Analysis Step 1As part of preprocessing we ensured certain things to make our software functional:• The input is a colored image• There are multiple faces with frontal view and upright orientation• The size of faces within the image should approximately be the same• Little deviation in brightness for all the faces within the image• Faces have to be greater than a certain size in the image so that facial features can be detected.• Standard dimension is not more than 1600 X 1200 px.
  10. 10. Step 2• Convert image to jjil.core.Image Where jjil means Jons Java Imaging Library.
  11. 11. Step 3Main Image R/G/B Image 8 bit grayscale
  12. 12. Step 4Applying Gray8DetectHaarMultiScale to our 8-bit grey image.
  13. 13. Final Output
  14. 14. Limititions• It can’t detect faces without frontal view and upright orientation
  15. 15. Future Plan• Design an intelligence system that can analyse objects.• Make them enable to see and feel like us.• Remove all its limitations and eager to develop this software.• Enable them to suggest us to make the best use of objects.• Empower media and security services.
  16. 16. Conclusion• Thanks all

×