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    Lab 8 Biomedical Imaging

    Uploaded by

    Abdul Rauf
    This document provides information about various image processing techniques including: 1. Converting RGB images to grayscale using rgb2gray. 2. Converting grayscale images to binary using im2bw and thresholding. 3. Removing small objects from binary images using bwareaopen. 4. Filling holes in binary images using imfill. 5. Creating structuring elements with strel for morphological operations. 6. Eroding and dilating images using imerode and imdilate with structuring elements. 7. Masking images to keep only regions inside a mask.

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    Lab 8 Biomedical Imaging

    Uploaded by

    Abdul Rauf
    47 views19 pages
    This document provides information about various image processing techniques including: 1. Converting RGB images to grayscale using rgb2gray. 2. Converting grayscale images to binary using im2bw and thresholding. 3. Removing small objects from binary images using bwareaopen. 4. Filling holes in binary images using imfill. 5. Creating structuring elements with strel for morphological operations. 6. Eroding and dilating images using imerode and imdilate with structuring elements. 7. Masking images to keep only regions inside a mask.

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    LAB 8

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    This document provides information about various image processing techniques including: 1. Converting RGB images to grayscale using rgb2gray. 2. Converting grayscale images to binary using im2bw and thresholding. 3. Removing small objects from binary images using bwareaopen. 4. Filling holes in binary images using imfill. 5. Creating structuring elements with strel for morphological operations. 6. Eroding and dilating images using imerode and imdilate with structuring elements. 7. Masking images to keep only regions inside a mask.

    Copyright:

    © All Rights Reserved
    Download as PDF, TXT or read online from Scribd
    Download as pdf or txt
    47 views19 pages

    Lab 8 Biomedical Imaging

    Uploaded by

    Abdul Rauf
    This document provides information about various image processing techniques including: 1. Converting RGB images to grayscale using rgb2gray. 2. Converting grayscale images to binary using im2bw and thresholding. 3. Removing small objects from binary images using bwareaopen. 4. Filling holes in binary images using imfill. 5. Creating structuring elements with strel for morphological operations. 6. Eroding and dilating images using imerode and imdilate with structuring elements. 7. Masking images to keep only regions inside a mask.

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    LAB 8

    Biomedical Imaging

    29-04-2021
    TERM PROJECT
    rgb2gray converts RGB images to grayscale by
    eliminating the hue and saturation information while
    retaining the luminance. I = rgb2gray(RGB) converts the
    truecolor image RGB to the grayscale intensity image I.
    newmap = rgb2gray(map) returns a grayscale colormap
    equivalent to map.
    im2bw (Convert image to binary image, based on
    threshold)
    • BW = im2bw(I,level) converts the grayscale image I to binary image
    BW, by replacing all pixels in the input image with luminance greater
    than level with the value 1 (white) and replacing all other pixels with
    the value 0 (black).

    • This range is relative to the signal levels possible for the image's class.
    Therefore, a level value of 0.5 corresponds to an intensity value
    halfway between the minimum and maximum value of the class.
    bwareaopen (Remove small objects from binary
    image)
    • BW2 = bwareaopen(BW,P) removes all connected components
    (objects) that have fewer than P pixels from the binary image BW,
    producing another binary image, BW2. This operation is known as an
    area opening.
    • Remove objects containing fewer than 50 pixels using bwareaopen
    function.

    • BW2 = bwareaopen(BW, 50);


    Imfill (Fill image regions and holes)
    • I = imread('coins.png');
    • figure
    • imshow(I)
    • title('Original Image')
    Imfill (Fill image regions and holes)
    • BW = imbinarize(I);
    • figure
    • imshow(BW)
    • title('Original Image
    Converted to Binary Image')
    Imfill (Fill image regions and holes)
    • Fill holes in the binary image and display the result.

    • BW2 = imfill(BW,'holes');
    • figure
    • imshow(BW2)
    • title('Filled Image')
    strel

    • A strel object represents a flat morphological structuring element,


    which is an essential part of morphological dilation and erosion
    operations.

    • A flat structuring element is a binary valued neighborhood, either 2-D


    or multidimensional, in which the true pixels are included in the
    morphological computation, and the false pixels are not. The center
    pixel of the structuring element, called the origin, identifies the pixel
    in the image being processed. Use the strel function (described
    below) to create a flat structuring element. You can use flat
    structuring elements with both binary and grayscale images.
    imerode Erode image

    • J = imerode(I,SE) erodes the grayscale, binary, or packed binary image


    I, returning the eroded image, J. SE is a structuring element object or
    array of structuring element objects, returned by the strel or
    offsetstrel functions.
    imerode Erode image
    imerode Erode image

    Original Image eroded Image


    Imdilate (Dilate image)

    • J = imdilate(I,SE) dilates the grayscale, binary, or packed binary image


    I, returning the dilated image, J. SE is a structuring element object or
    array of structuring element objects, returned by the strel or
    offsetstrel functions.
    Dilate image

    Original Image dilated Image


    MASKING
    • Will keep only the part of the image that's inside the mask, zero
    outside mask.
    ??

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