Basic Geometric Transformations

Basic Geometric Transformations

The process to change the geometry of each object by changing its size, position or orientation. These operations are called geometric transformations.

Translation

We translate objects in the (x, y) plane to new positions by adding translation vectors to the coordinates of their vertices.

x’ = x + d x
y’ = y + d y

In matrix form this is:

Scaling

Objects can be stretched or shrinked by scaling their vertices. Their coordinates have to be multiplied by the read more

Basic Transformations on image

Basic Transformations on image

Enhancing an image provides better contrast and a more detailed image as compare to non enhanced image. Image enhancement has very applications. It is used to enhance medical images, images captured in remote sensing , images from satellite e.t.c

The transformation function has been given below

s = T ( r )

where r is the pixels of the input image and s is the pixels of the output image. T is a transformation function that maps each value of r to each value of s.

A) Logarithmic transformations:

Logarithmic read more

Program to plot a Histogram

Program to plot a Histogram

A histogram is a graph. A graph that shows frequency of anything. Usually histogram have bars that represent frequency of occurring of data in the whole data set.

Code:

clear all;
clc;
close all;
a=imread(‘E:\Final\image.jpg’);
b=zeros(1,256);
[row,col]=size(a);

for x=1:1:row
for y=1:1:col
if a(x,y)<1
continue;
else
t=a(x,y);
end
b(t)=b(t)+1;
end
end

subplot(1,2,1);
imshow(uint8(a));
title(‘Original Image’);

subplot(1,2,2);
bar(b);
title(?Histogram read more

To apply Histogram Equalization on image

Program to apply Histogram Equalization on image

Histogram equalization is used to enhance contrast. It is not necessary that contrast will always be increase in this. There may be some cases were histogram equalization can be worse. In that cases the contrast is decreased.

Code:

clear all
clc
I=imread(?cameraman.tif?);
I=double(I);
maximum_value=max((max(I)));
[row col]=size(I);
c=row*col;
h=zeros(1,300);
z=zeros(1,300);
for n=1:row
for m=1:col
if I(n,m) == 0
I(n,m)=1;
read more

Morphological Operations on Image

Morphological Operations on Image

Morphological image processing is a collection of non-linear operations related to the shape or morphology of features in an image. According to Wikipedia, 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. Morphological operations can also be applied to greyscale images such that their light transfer functions are unknown and therefore their absolute pixel values read more

Applying the DFT & IDFT on the image matrix

Applying the DFT and IDFT on the image matrix

DFTDiscrete Fourier transform [ From Wikipedia, the free encyclopedia]

The DFT is the most important discrete transform, used to perform Fourier analysis in many practical applications. In digital signal processing, the function is any quantity or signal that varies over time, such as the pressure of a sound wave, a radio signal, or daily temperature readings, sampled over a finite time interval (often defined by a window function). In image processing, the samples read more