The slide was prepared on the purpose of presentation of our project face detection highlighting the basics of theory used and project details like goal, approach. Hope it's helpful.

1. CSE 2100
Software Development Project 1
Project Title
Face Detection

2. Supervisor
Mr. Md. Aminul Haque Akhand
Assistant Professor
Department of Computer Science and Engineering
Khulna University of Engineering and Technology
Credit: Abu Saleh Md. Musa (0907013)
Sanjoy Dutta (0907008)

3. Objectives
• The objective of our project is to design
software that can detect human faces from an
image.

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. 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. Examples of Implementation 1
Picasa Photo Viewer
(people panel)

7. Examples of Implementation 2
• Facebook Tagging

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. Step by Step Analysis
Step 1
As 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. Step 2
• Convert image to jjil.core.Image
Where jjil means Jon's Java Imaging
Library.

11. Step 3
Main Image R/G/B Image 8 bit grayscale

12. Step 4
Applying Gray8DetectHaarMultiScale to
our 8-bit grey image.

13. Final Output

14. Limititions
• It can’t detect faces without frontal view
and upright orientation

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. Conclusion
•
Thanks all