Upcoming SlideShare
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×
Saving this for later? Get the SlideShare app to save on your phone or tablet. Read anywhere, anytime – even offline.
Standard text messaging rates apply

# Matlab Feature Extraction Using Segmentation And Edge Detection

12,556

Published on

Matlab Feature Extraction Using Segmentation And Edge Detection

Matlab Feature Extraction Using Segmentation And Edge Detection

Published in: Technology, Sports
11 Likes
Statistics
Notes
• Full Name
Comment goes here.

Are you sure you want to Yes No
Views
Total Views
12,556
On Slideshare
0
From Embeds
0
Number of Embeds
1
Actions
Shares
0
0
2
Likes
11
Embeds 0
No embeds

No notes for slide

### Transcript

• 1. Matlab:Feature Extraction Using Segmentation and Edge Detection
• 2. Detecting Edges Using the edge Function
In an image, an edge is a curve that follows a path of rapid change in image intensity.
• 3. Detecting Edges Using the edge Function
• 4. imshow(I);
• 5. BW1 = edge(I,'sobel');
• 6. BW2 = edge(I,'canny');
• 7. figure, imshow(BW1) ;
• 8. figure, imshow(BW2)
• Detecting Edges Using the edge Function
• 9. imshow(I);
• 10. BW1 = edge(I,'sobel');
• 11. BW2 = edge(I,'canny');
• 12. figure, imshow(BW1) ;
• 13. figure, imshow(BW2)
• Detecting Edges Using the edge Function
The radon function computes projections of an image matrix along specified directions.
&gt;&gt; I=zeros(100,100);
&gt;&gt; I(40:60, 40:60)=1;
&gt;&gt; imshow(I);
&gt;&gt; figure,plot(xp,R);
&gt;&gt; I=zeros(100,100);
&gt;&gt; I(40:60, 40:60)=1;
&gt;&gt; imshow(I);
&gt;&gt; figure,plot(xp,R);
The iradon function inverts the Radon transform and can therefore be used to reconstruct images. iradon reconstructs an image from parallel-beam projections. In parallel-beam geometry, each projection is formed by combining a set of line integrals through an image at a specific angle.
P = phantom(def, n) generates an image of a head phantom that can be used to test the numerical accuracy of radon and iradon or other two-dimensional reconstruction algorithms.
&gt;&gt; P=phantom(256);
&gt;&gt; imshow(P)
&gt;&gt; theta1 = 0:10:170; [R1,xp] = radon(P,theta1);
theta2 = 0:5:175; [R2,xp] = radon(P,theta2);
theta3 = 0:2:178; [R3,xp] = radon(P,theta3);
&gt;&gt; figure, imagesc(theta3,xp,R3); colormap(hot); colorbar
xlabel(&apos; heta&apos;); ylabel(&apos;xprime&apos;);
imshow(I1);
figure, imshow(I2);
figure, imshow(I3);