This document discusses morphological image processing techniques. It defines morphological operations as non-linear operations related to the shape or morphology of features in an image. Specifically, it describes dilation, opening, and closing on binary images. Dilation expands shapes by adding pixels to boundaries, acting as a local maximum filter. Opening removes narrow connections between regions by first eroding and then dilating. Closing fills narrow holes by first dilating and then eroding. Both opening and closing use the same structuring element for the erosion and dilation.

1. Topic:-Morphological Image
Processing
Subject:-Digital Image Processing
Name:-Abhishek Manmode
Year:-4𝑇𝐻 (B)
Roll No:-29

2. Contents
 Morphological Image Processing
 Dilation
 Opening
 Closing on binary images

3. Morphological Image Processing
 Binary images (consists of pixels that can have one of exactly two colors,
usually black and white) may contain numerous imperfections. In particular,
noises and textures can be distorted when the binary regions produced by
simple threshold.
 Morphological Operations in Image Processing pursues the goals of removing
these imperfections by accounting for the form and structure of the image.
 A collection of non-linear operations related to the shape or morphology of
features in an image is known as Morphological
 Operation in Image Processing. Morphological operations rely only on the
relative ordering of pixel values, not on their numerical values, and therefore
are especially suited to the processing of binary images.

4. Dilation (represented by the symbol ⊕)
 The assigned structuring element is used for probing and expanding the shapes
contained in the input image. In Specific, it acts like local maximum filter.
Dilation has the opposite effect to erosion . It adds a layer of pixels to both the
inner and outer boundaries of regions.
 That is, the value of the output pixel is the maximum value of all pixels in the
neighborhood. In a binary image, a pixel is set to 1 if any of the neighboring
pixels have the value 1. Morphological dilation makes objects more visible and
fills in small holes in objects.

5. Opening
 It is achieved by first eroding an image and then dilating it. Opening removes any
narrow connections and lines between two regions.
The opening operation erodes an image and then dilates the eroded image,
using the same structuring element for both operations. Morphological
opening is useful for removing small objects from an image while
preserving the shape and size of larger objects in the image.

6. Closing (A • B=(A⊕B)⊖B)
 It is done by first dilating the image and then eroding it. The order is the
reverse of opening. Closing fills up any narrow black regions or holes in the
image.
 The closing operation dilates an image and then erodes the dilated image, using
the same structuring element for both operations. Morphological closing
is useful for filling small holes from an image while preserving the shape and
size of the objects in the image.

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