Matlab Image Processing Projects PDF

Matlab is a both computer programming language and a software environment for using the language in an effective manner. Matlab is a fourth generation programming language tool. Main part of matlab is also called as Matlab toolboxes.  Mathworks laboratory is now responsible for development, sale and supports.

 

Supports of Matlab

  • Matlab should supports two aspects of image processing
  • Images are prepared for measurement of the features and structures present
  • Visual appearance of images to a human viewer can be improved

 

Image Processing Fields:

  • Computer Graphics
  • Computer vision
  • Image Processing

 

Applications of Image Processing:

  • Speed Controller
  • Mobile Robots
  • Spatial Block Partitioning
  • Vehicle Detection System
  • Defense
  • Security
  • Astronomical application

Image Processing Typical Operations:

  • Colorization
  • Photo Restoration
  • Image Masking
  • Removing objects, background and persons
  • Image Re-touching, cleaning and cloning
  • Portraitize, glamorize, Adding Motion Effects
  • Image processing toolbox is a collection of functions

 

Techniques Used in Matlab:

  • Camera Calibration
  • Real-Time Stereo Vision
  • Parameter Estimation
  • Gauss Newton Optimization
  • Wavelet transformation
  • Ensemble Learning.

Example Code for Morphological Operations:
Dilating an Image:
Read an image BW1 = imread(‘circbw.tif’);
Creating a structuring element
se = strel(‘diamond’,3)
Structuring element decomposition
sel = strel(‘diamond’,4)seq = getsequence(sel)
Dilating a image
BW2 = imdilate(BW,SE)
Eroding an Image:
Read an image
BW1 = imread(‘circbw.tif’);
Create structuring element
SE = strel(‘arbitrary’,eye(5));
Erode function
BW2 = imerode(BW1,SE);Restore the functionimshow(BW1)figure, imshow(BW2)

Example Code for ROI:
Binary Mask Creation Using ROI Object
img = imread(‘pout.tif’);h_im = imshow(img);e = imellipse(gca,[55 10 120 120]);BW = createMask(e,h_im);
Example Code for Image Quality Comparison:
Read an image
I = imread(‘cameraman.tif’);
Check quality of an image
ssimValues = zeros(1,10);qualityFactor = 10:10:100;for i = 1:10 imwrite(I,’compressedImage.jpg’,’jpg’,’quality’,qualityFactor(i)); ssimValues(i) = ssim(imread(‘compressedImage.jpg’),I);end
Plot the results
plot(qualityFactor,ssimValues,’b-o’);xlabel(‘Compression Quality Factor’);ylabel(‘SSIM Value’);