Image Segmentation
12
Image Image Segmentation Segmentation Chin-Ya Huang Chin-Ya Huang Mon-Ju Wu Mon-Ju Wu ECE 533 Final Project, Fall ECE 533 Final Project, Fall 2006 2006 University of Wisconsin – University of Wisconsin – Madison Madison
description
Image Segmentation. Chin-Ya Huang Mon-Ju Wu ECE 533 Final Project, Fall 2006 University of Wisconsin – Madison. Methodology. Acquire the color information and the edge information separately. Use hue, saturation and intensity to get color information. - PowerPoint PPT Presentation
Transcript of Image Segmentation
Image Image SegmentationSegmentation
Chin-Ya Huang Chin-Ya Huang Mon-Ju WuMon-Ju Wu
ECE 533 Final Project, Fall 2006ECE 533 Final Project, Fall 2006University of Wisconsin – MadisonUniversity of Wisconsin – Madison
MethodolMethodologyogy
1)1) Acquire the color Acquire the color information and the edge information and the edge information separately.information separately.
2)2) Use hue, saturation and Use hue, saturation and intensity to get color intensity to get color information.information.
3)3) Use the Matlab “edge” Use the Matlab “edge” command to extract the command to extract the image boundary.image boundary.
4)4) Combine the above result by Combine the above result by getting the union of (2) and getting the union of (2) and (3).(3).
5)5) Final modification.Final modification.
MethodolMethodologyogy
Original Image
Texture Extraction
Shape Extraction
Intersaction
End
Start
Extracted Edge
Separate image into H. S. I components
ExampleExample
Target:Target: Extract the Extract the
image of the image of the soccer player soccer player out from the out from the entire image.entire image.
Step 1 : Using HSI as a Step 1 : Using HSI as a thresholdthreshold
A)A) Cut partial Cut partial images to images to compute the compute the HSI values.HSI values.
B)B) Set the Set the threshold threshold value.value.
C)C) Examine Examine through the through the image to image to acquire the acquire the color color information.information.
Step 2 : Using Matlab “edge” Step 2 : Using Matlab “edge” commandcommand
A)A) Use Matlab “edge” Use Matlab “edge” command to extract the command to extract the course edges.course edges.
B)B) Use Matlab “imfill” Use Matlab “imfill” command to fill the area command to fill the area whose surrounding course whose surrounding course edges make a closure.edges make a closure.
edgeedge imfill(edimfill(edge)ge)
Step 3 : Combine the above Step 3 : Combine the above imagesimages
A)A) Get the Get the union of the union of the images from images from Step 1 and Step 1 and Step 2.Step 2.
B)B) Combine the Combine the color color information information and the and the edge.edge.
Step 4 : Final modificationStep 4 : Final modification
A)A) Perform Perform dilate on dilate on “edge” make “edge” make sure all the sure all the separate line separate line segments are segments are connected. connected.
B)B) Use “imfill” Use “imfill” command to command to fill the area fill the area inside the inside the boundary.boundary.
Step 4 : Final modification Step 4 : Final modification (cont.)(cont.)C)C) Intersect the Intersect the
image from image from (B) with the (B) with the image from image from Step 3 to Step 3 to remove the remove the noise.noise.
D)D) Image from Image from (C) is the (C) is the final result.final result.
Final Final ResultResult
Original Original ImageImage
Future WorkFuture Work
A)A) Develop a more powerful Develop a more powerful algorithm to perform algorithm to perform interpolation in order to interpolation in order to connect the disconnected connect the disconnected line segment.line segment.
B)B) Find other ways to segment Find other ways to segment image other than using HSI.image other than using HSI.
C)C) Develop a more powerful Develop a more powerful algorithm for noise removal.algorithm for noise removal.
