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# CIS581 Presentation Morphological Operations - PowerPoint PPT Presentation

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 PresentationMorphological Operations

Presented by: Xueyan Li

Supervised by: Longin Jan Lateckie

• 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

• 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.

• Dilation

• Erosion

• Opening

• Closing

• 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.

• 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 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

%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 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

%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 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

%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 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

%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)

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

Original imageafter 1 dilation

Matlab program iterative operation of dilation (1)

after 5th dilations after inf dilations

Original imageafter 1 dilation

Matlab program iterative operation of dilation (2)

after 5th dilations after inf dilations

Original imageafter 1 erosion

Matlab program iterative operation of erosion (1)

after 5th erosions after inf erosions

Original imageafter 1 erosion

Matlab program iterative operation of erosion (2)

after 5th erosions after inf erosions

Original imageafter 1 opening

Matlab program iterative operation of opening (1)

after 5th openings after inf openings

Original imageafter 1 opening

Matlab program iterative operation of opening (2)

after 5th openings after inf openings

Original imageafter 1 closing

Matlab program iterative operation of closing (1)

after 5th closings after inf closnings

Original imageafter 1 closing

Matlab program iterative operation of closing (2)

after 5th closings after inf closings

Morphological operations on gray-level image

Original imageImage after dilationImage after erosion

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!