| CSE 576: Image Understanding
Autumn 1998
|
CSE 576 Final Project
During the second half of the quarter you will do a 4-5
week class project, to allow you to do something with more depth
than the small assignments. Projects are to be defined by you, proposed
to me, and approved before starting. You can start any time, but
the official due date for proposals is October 29.
You can choose something that comes from your own interests, or there
are default projects such as segmentation of images according to color
and texture properties. (See below.)
The idea of the project is to design and implement a computer vision
system that can do the task you have chosen. You may use packages
for utilities whenever possible, but there should be
some programming of your own in the project, too. You should not just
get it working on one image, but apply it to a small set of test images
and evaluate the results.
The final project is due on December 11 at 5pm, by which time
you should have turned in a typed project report of 5-10 pages.
Project reports should contain at least the following:
- Introduction explaining the problem you tried to solve
- Discussion of any relevant literature you have read
- Description of the techniques you used to solve the problem
- Experiments and Results
- Conclusions and Future Work
- Appendix with the code you developed
Default Project
The default project is a segmentation system that uses both color
and texture to segment color images into regions. A region is
an area of the image that is deemed homogeneous in both color
and texture according to the method used. You can implement a method
from the literature (or more than one to compare if they are not very
difficult) or can you choose to develop your own method. We have
lots of color images including my football sequences, a set of paintings
from Italy, and a set of gem and other exhibit images from the Smithsonian
and more.
Examples of Past Student Projects
- Texture-based Image Retrieval
- Automated Volume Measurement for Glass Capillaries
- Motion Segmentation based on Optical Flow and Model Estimation
- Registration of Medical Images
- Hand-printed Character Recognition
- OCR for Hebrew Fonts
- Binary image shape features
- Template Matching Algorithm Study
- Color Segmentation of Football Images
- Del Bimbo Shape Distance
- Tissue Elasticity from Sonogram Images
- Recognizing 3D Industrial Objects from 2D Views
- Feature-Based Stereo Matching
- Color Photometric Stereo
- 4-camera Active Stereo with Light Stripes