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CIS581 Presentation Morphological Operations. Presented by: Xueyan Li Supervised by: Longin Jan Lateckie. Presentation Outline. Terminology and properties of Morphology Operations Structure element Four morphological Principles Iterative Morphological Operations

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cis581 presentation morphological operations

CIS581 PresentationMorphological Operations

Presented by: Xueyan Li

Supervised by: Longin Jan Lateckie

presentation outline
Presentation Outline
  • Terminology and properties of Morphology Operations
  • Structure element
  • Four morphological Principles
  • Iterative Morphological Operations
  • Matlab Programs and results images for each operation
introduction morphology operations
Introduction---Morphology Operations
  • Terminology

Morphology:a broad set of image processing operations that process images based on shapes.

Morphological operations apply a structuring elements to an input image, creating an output image of the same size.

  • Properties

Morphological operations simplify images, and quantify and preserve the main shape characteristics of objects.

four morphological principles
Four morphological principles
  • Dilation
  • Erosion
  • Opening
  • Closing
relationship of four operations
Relationship of four operations
  • Dilation and Erosion are the basic operations, can be combined into more complex sequences.
  • Erosion and dilation are not invertible operations ---if an image is eroded and dilated, the original image is not re-obtained.
  • The combination of Erosion and dilation constitutes new operations ----opening and closing. They are the most useful morphological filtering.
structuring element
Structuring element
  • Morphological operations can be customized for an application by the proper selection of the structuring element, which determines exactly how the object will be dilated or eroded.
  • matlab function strel() can create many kinds of structuring element:

dish-shaped,

diamond-shaped,

ball-shaped,

square

flat linear with length LEN

arbitrary flat or a nonflat with the specified neighborhood

dilation
Dilation

Dilation allows objects to expand, then potentially filling in small holes and connecting disjoint object.

Performance: laying the structuring element on the image and sliding it across the image.

1) If the origin of the structuring element coincides with a ‘0’ in the image, there is no change; move to the next pixel.

2) If the origin of the structuring element coincides with a ‘1’ in the images, perform the OR logic operation on all pixels within the structuring element.

matlab programming dilation
original image (above)Matlab programming ---dilation

%Read image

I = imread(‘ford.tiff');

figure('Name', 'original');

imshow(I);

%create structuring elements

% 11-by-11 square

se1 = strel('square',11);

%Apply dilation operation

figure('Name', 'Dilate');

Idilate1 = imdilate(I,se1);

%Show the result image

subplot(1,1,1), imshow(Idilate1), title('11x11 square');

Image after dilation (below)

erosion
Erosion

Erosion shrinks objects by etching away (eroding) their boundaries.

Performance:

1) If the origin of the structuring element coincides with a ‘0’ in the image, there is no change; move to the next pixel.

2) If the origin of the structuring element coincides with a ‘1’ in the image, and any of the ‘1’ pixels in the structuring element extend beyond the object (‘1’ pixels) in the image, then change the ‘1’ pixel in the image to a ‘0’;

matlab programming erosion
original image (above)Matlab programming ---erosion

%Read image

I = imread(‘ford.tiff');

figure('Name', 'original');

imshow(I);

%create structuring elements

% 11-by-11 square

se1 = strel('square',11);

%Apply erosion operation

figure('Name', 'Erode');

Ierode1 = imerode(I,se1);

%Show the result image

subplot(1,1,1), imshow(Ierode1), title('11x11 square');

Image after erosion (below)

opening
Opening

Opening consists of an erosion followed by a dilation and can be used to eliminate all pixels in regions that are to small to contain the structuring element.

In this case the structuring element is often called a probe, because it is probing the image looking for small objects to filter out of the image.

matlab programming opening
original image (above)Matlab programming--- opening

%Read image

I = imread(‘ford.tiff');

figure('Name', 'original');

imshow(I);

%create structuring elements

% 11-by-11 square

se1 = strel('square',11);

%Apply the open opration

figure('Name', 'Open');

Iopen1 = imopen(I,se1);

%Show the result image

subplot(1,1,1), imshow(Iopen1), title('11x11 square');

Image after opening (below)

closing
Closing

Closing consists of a dilation followed by an erosion and connects objects that are close to each other. It can be used to fill in holes and small gaps.

matlab programming closing
original image (above)Matlab programming ---closing

%Read image

I = imread(‘ford.tiff');

figure('Name', 'original');

imshow(I);

%create structuring elements

% 11-by-11 square

se1 = strel('square',11);

%Apply close operation

figure('Name', ‘Close');

Iclose1 = imclose(I,se1);

%Show the result image

subplot(1,1,1), imshow(Iclose1), title('11x11 square');

Image after closing (below)

iterative morphological operations
Iterative Morphological Operations

We can apply one or several operations to an image iteratively.

InputImage ---(apply an operation) outputImage1

---(apply the operation again) outputImage2

…and so on…..until get your desired image

morphological operations on gray level image
Morphological operations on gray-level image

Original imageImage after dilationImage after erosion

my programming files
My programming files

1. morphor.m

2. bwmorhpr.m

If you are more interested in this topic, you can try to play the source code with a updated Matlab. I’m sure a lot of fun there!