Pruning in Image Processing
#1

Presented by:
Sheikh Qaisar Ayub

[attachment=12149]
Pruning in Image Processing
Pruning
What ?

A post processing Operation on images
Thinning and skeltonization algorithms tends to leave the parasitic components
Parasitic Components
Put the picture from the net.
• Pruning
Problem
Our task is to recognize the hand written characters
Solution
Find the skeleton of each character
During the process of skeleton some of the parasitic components associated in each character
These parasitic components derived due to the non uniformalities in the strokes composing the character
• Pruning
Parasitic
• Pruning
Achievements
1. What is pruning
2. Parasitic Components
• Pruning
To understand the pruning algorithm we take an example of recognizing the handwritten character ‘a’
Pruning
• Pruning

Algorithm
Step-01
Suppress the parasitic components by eliminating the end points
By applying the thinning algorithm on the image we can get endpoints
Mathematically the thinning algorithm can be written as
X1 = A {B}
Pruning
Algorithm
Step-01
X1 = A {B}
B := Structuring element
{ } := Represent the iteration
A := Input Image
:= Hit or Miss Translation
Pruning
Algorithm
Step-01
X1 = A {B}
Structuring element {B} = B1 B2 B3 B4 B5 B6 B7 B8
B1
B2
B3
Pruning
Algorithm
Step-01
X1 = A {B}
Structuring element {B} = B5 B6 B7 B8
B5 :=
B6:=
B7:=
B8:=
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