Matlab Feature Extraction Using Segmentation And Edge Detection
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This document discusses several image processing techniques in Matlab: 1) Edge detection using the edge function and Sobel and Canny edge detection algorithms. 2) The radon transform which computes projections of an image along specified directions and the inverse radon transform used to reconstruct images from projections. 3) Marker-controlled watershed segmentation which separates touching objects in an image using morphological operations like gradients and markers.
![Radon Transform>> I=zeros(100,100);>> I(40:60, 40:60)=1;>> imshow(I);>> [R,xp] = radon(I,0);>> figure,plot(xp,R);](https://image.slidesharecdn.com/matlabfeatureextractionusingsegmentationandedgedetection-091213023613-phpapp02/85/Matlab-Feature-Extraction-Using-Segmentation-And-Edge-Detection-15-320.jpg)
![Radon Transform>> I=zeros(100,100);>> I(40:60, 40:60)=1;>> imshow(I); >> [R,xp] = radon(I,45);>> figure,plot(xp,R);](https://image.slidesharecdn.com/matlabfeatureextractionusingsegmentationandedgedetection-091213023613-phpapp02/85/Matlab-Feature-Extraction-Using-Segmentation-And-Edge-Detection-16-320.jpg)
Matlab Feature Extraction Using Segmentation And Edge Detection
- 1. Matlab:Feature Extraction Using Segmentation and Edge Detection
- 2. Detecting Edges Using the edge FunctionIn an image, an edge is a curve that follows a path of rapid change in image intensity.
- 3. Detecting Edges Using the edge FunctionI = imread(‘dmt.jpg');
- 4. imshow(I);
- 8. figure, imshow(BW2)Detecting Edges Using the edge FunctionI = imread(‘bird.png');
- 9. imshow(I);
- 13. figure, imshow(BW2)Detecting Edges Using the edge Function
- 14. Radon TransformThe radon function computes projections of an image matrix along specified directions.
- 15. Radon Transform>> I=zeros(100,100);>> I(40:60, 40:60)=1;>> imshow(I);>> [R,xp] = radon(I,0);>> figure,plot(xp,R);
- 16. Radon Transform>> I=zeros(100,100);>> I(40:60, 40:60)=1;>> imshow(I); >> [R,xp] = radon(I,45);>> figure,plot(xp,R);
- 17. Inverse Radon TransformThe 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.
- 18. Inverse Radon TransformP = 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.
- 19. Inverse Radon Transform>> P=phantom(256);>> imshow(P)>> 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);>> figure, imagesc(theta3,xp,R3); colormap(hot); colorbarxlabel('\theta'); ylabel('x\prime');>> I1 = iradon(R1,10);I2 = iradon(R2,5);I3 = iradon(R3,2);imshow(I1);figure, imshow(I2);figure, imshow(I3);
- 21. Marker-Controlled Watershed SegmentationSeparating touching objects in an image is one of the more difficult image processing operations. The watershed transform is often applied to this problem.
- 22. Marker-Controlled Watershed SegmentationStep 1: Read in the Color Image and Convert it to Grayscale
- 23. Step 2: Use the Gradient Magnitude as the Segmentation Function
- 24. Step 3: Mark the Foreground Objects
- 25. Step 4: Compute Background Markers
- 26. Step 5: Compute the Watershed Transform of the Segmentation Function.
- 27. Step 6: Visualize the ResultMarker-Controlled Watershed Segmentation