Experimental results 1 k means clustering on rgb

Info icon This preview shows pages 4–14. Sign up to view the full content.

View Full Document Right Arrow Icon
Experimental results: 1. K-means clustering on RGB modeled image Image 1 original retinal image red channel green channel blue channel image labeled by cluster index
Image of page 4

Info icon This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
Image 2 original retinal image red channel green channel blue channel image labeled by cluster index
Image of page 5
2. K-means clustering on HSI modeled image
Image of page 6

Info icon This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
3. Thresholding on RGB modeled image Image 1 original retinal image red channel green channel blue channel taking green channel binary disk image morphological processed binary disk segmented disk image
Image of page 7
Image 2 original retinal image red channel green channel blue channel taking green channel binary disk image morphological processed binary disk segmented disk image
Image of page 8

Info icon This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
4. Thresholding on HSI modeled image Image 2 original image Hue Saturation Intensity threshold for hue threshold for saturation threshold for intensity morphological processed binary disk segmented disk image
Image of page 9
Image 2 original image Hue Saturation Intensity threshold for hue threshold for saturation threshold for intensity morphological processed binary disk segmented disk image
Image of page 10

Info icon This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
6. Thresholding on RGB modeled image with combination of layers original retinal image red channel green channel blue channel Extracting red layer Extracting green layer Extracting blue layer layer binary disk image for red layer
Image of page 11
binary disk image morphological processed binary disk(green layer) segmented disk image
Image of page 12

Info icon This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
Code: 1. K-means clustering on RGB modeled image [fname path]=uigetfile( '*.tif' , 'Select an image' ); % [FILENAME, PATHNAME, FILTERINDEX] = UIGETFILE(FILTERSPEC, TITLE) fname=strcat(path,fname); im=imread(fname); figure subplot(2,2,1) imshow(im); title( 'original retinal image' ); impixelinfo; %% color channel seperation imR=im; imR(:,:,2:3)=0; subplot(2,2,2) imshow(imR); title( 'red channel' ); imG=im; imG(:,:,1:2:3)=0; subplot(2,2,3) imshow(imG) title( 'green channel' ); imB=im; imB(:,:,1:2)=0; subplot(2,2,4) imshow(imB) title( 'blue channel' ); ab = double(imG(:,:,2:3)); %%converting green layer into double nrows = size(ab,1); %%extracting rows ncols = size(ab,2); %%extracting cols ab = reshape(ab,nrows*ncols,2); %%reshaping to form 2D image nColors = 3; %%no of clusters % repeat the clustering 3 times to avoid local minima [cluster_idx, cluster_center] = kmeans(ab,nColors, 'distance' ,
Image of page 13
Image of page 14
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}

What students are saying

  • Left Quote Icon

    As a current student on this bumpy collegiate pathway, I stumbled upon Course Hero, where I can find study resources for nearly all my courses, get online help from tutors 24/7, and even share my old projects, papers, and lecture notes with other students.

    Student Picture

    Kiran Temple University Fox School of Business ‘17, Course Hero Intern

  • Left Quote Icon

    I cannot even describe how much Course Hero helped me this summer. It’s truly become something I can always rely on and help me. In the end, I was not only able to survive summer classes, but I was able to thrive thanks to Course Hero.

    Student Picture

    Dana University of Pennsylvania ‘17, Course Hero Intern

  • Left Quote Icon

    The ability to access any university’s resources through Course Hero proved invaluable in my case. I was behind on Tulane coursework and actually used UCLA’s materials to help me move forward and get everything together on time.

    Student Picture

    Jill Tulane University ‘16, Course Hero Intern