1. Chin-Ya Huang Mon-Ju Wu
Image Segmentation
Chin-Ya Huang Mon-Ju Wu
ECE 533 Final Project, Fall 2006
University of Wisconsin – Madison

2. Methodology
Acquire the color information and the edge information separately.
Use hue, saturation and intensity to get color information.
Use the Matlab “edge” command to extract the image boundary.
Combine the above result by getting the union of (2) and (3).
Final modification.

3. Methodology

4. Example
Target:
Extract the image of the soccer player out from the entire image.

5. Step 1 : Using HSI as a threshold
Cut partial images to compute the HSI values.
Set the threshold value.
Examine through the image to acquire the color information.

6. Step 2 : Using Matlab “edge” command
Use Matlab “edge” command to extract the course edges.
Use Matlab “imfill” command to fill the area whose surrounding course edges make a closure.

7. edge
imfill(edge)

8. Step 3 : Combine the above images
Get the union of the images from Step 1 and Step 2.
Combine the color information and the edge.

9. Step 4 : Final modification
Perform dilate on “edge” make sure all the separate line segments are connected.
Use “imfill” command to fill the area inside the boundary.

10. Step 4 : Final modification (cont.)
Intersect the image from (B) with the image from Step 3 to remove the noise.
Image from (C) is the final result.

11. Final Result
Original Image

12. Future Work
Develop a more powerful algorithm to perform interpolation in order to connect the disconnected line segment.
Find other ways to segment image other than using HSI.
Develop a more powerful algorithm for noise removal.