Download presentation

Presentation is loading. Please wait.

Published byIzaiah Rollie Modified over 2 years ago

1
Imageprocessing An introduction

2
What is image processing? image analysis patron recognition graphical manipulation datacompression data transmission multi media applications

3
2. Global Image operation Histogram Stretching Histogram Equalization Binarization/ Thresholding Math on images

4
Histogram

5
Histogram with MATLAB %y=imread('zand.jpg'); zon=zongray('mushroom2.jpg'); %zon equals contents of 'picuter' arraywaarde=zeros(1,256); % make an empty array[l,b]=size(zon); % measure picture size figure(1); % make a new picture image(zon); % show picture colormap(gray(256)); % set gray colormap for i=1:l % Go for every pixel from 1 to for j=1:b % Take care MATLAB arrays cannot start with 0! a=double(zon(i,j)); % Convert pixelvalue to double calculating with pixelvalues waarde(a+1)=waarde(a+1)+1; % if value is certain value add 1 for that value end figure(2); % Make new (second figure) bar(waarde); % Give a bargraph of the result

6
Stretching

7
Stretching(2) y=(x-64)*4

8
3. Local Operations Smoothing Low pass filtering Edge detection Directional edge detecting Min-max operation Sharpening Special filters

9
Local operation Make a new image depending on pixels in the neigtbourhood filtering.gif

10
Smoothing with mean filter filtering.gif

11
Smoothing with Gaussian Low pass

12
Edge detection with Laplacian operator

13
Edge detection with Laplacian operator(2) L[f(x,y)] = d 2 f / dx 2 + d 2 f / dy 2 d 2 f / dx 2 = f(x+1, y) - 2f(x, y) + f(x-1, y) d 2 f / dy 2 = f(x, y+1) - 2f(x, y) + f(x, y-1) L[f(x,y)] = -4f(x, y) + f(x+1), y) + f(x-1, y) + f(x, y+1) + f(x, y-1) (approx.)

14
Directional Edge Detection

15
demo Filters.exe

16
4. Morphologie Erosion Dilitation Opening / closing Conditional erosion Skeleton

17
Erosion and Dilation 8 and 4 connect influence 8-connect4-connect

18
Erosion

19
Dilation

20
Erosion 8-connected

21
Dilation 8 connected

22
Opening and closing

23
Erosion and Dilation with threshold threshold=1 (at least 8 must be there)

24
Erosion Dilation applications Opening and closing. ( For correct counting ) Deletes noise pixels Makes connection at border lines Skeleton Perimeter determination

25
Conditional Erosion Keep the last pixel Keep connectednes Keep the end-pixel of a string of pixels with 1 pixel

26
Keep the last pixel Reduction to 1 point

27
Skeleton example application:characterrecognition

28
Image analysis Labeling Contour analysis

Similar presentations

OK

Image Processing Part II. 2 Classes of Digital Filters global filters transform each pixel uniformly according to the function regardless of its location.

Image Processing Part II. 2 Classes of Digital Filters global filters transform each pixel uniformly according to the function regardless of its location.

© 2017 SlidePlayer.com Inc.

All rights reserved.

Ads by Google