![TO READ AN IMAGE
a =imread('cameraman.tif');
imshow(a);
ADD TWO IMAGES
I = imread(‘rice.tif');
J = imread('cameraman.tif');
K = imadd(I,J,'uint16');
imshow(K,[])](https://image.slidesharecdn.com/imageprocessingonmatlabpresentation-160301125221/85/Image-processing-on-matlab-presentation-17-320.jpg)
![CONVERT IMAGE TO GRAY AND
BINARY
clc;
clear;
close all
a= imread(‘peppers.png');
subplot(2,2,1);
imshow(a);
subplot(2,2,2);
b=imresize(a,[256 256]);
imshow(b);
subplot(2,2,3);
c=rgb2gray(b);
imshow(c);
subplot(2,2,4);
d=im2bw(c);
imshow(d);](https://image.slidesharecdn.com/imageprocessingonmatlabpresentation-160301125221/85/Image-processing-on-matlab-presentation-18-320.jpg)
![RGB COMPONENT
a=imread(‘peppers.png’)
subplot(2,2,1);
imshow(a);
[r c p]=size(a)
R=a;
G=a;
B=a;
R(:,:,2:3)=0;
subplot(2,2,2);
imshow(R);
G(:,:,1)=0;
G(:,:,3)=0;
subplot(2,2,3);
imshow(G);
B(:,:,1)=0;
B(:,:,2)=0;
subplot(2,2,4);
imshow(B);](https://image.slidesharecdn.com/imageprocessingonmatlabpresentation-160301125221/85/Image-processing-on-matlab-presentation-19-320.jpg)
Image processing on matlab presentation
- 1. IMAGE PROCESSING ON MATLAB PRESENTED BY RM.NAATCHAMMAI (III-ECE)
- 2. ABSTRACT 1. MATLAB introduction-commands-operators- functions-GUI 2. Image Processing Basics formats of image, colors 3. Techniques:enhancement,restoration,water marking,cryptography,steganography,image fusions 4. Algorithms-example programs 5. Real-time applications-project based ideas.
- 3. Introduction MATLAB MATrix LABoratory Developed by CleveMoler in 1984 as a teaching tool High performance language for technical computing Typical uses are, numerical computation Data analysis ,plotting and visualization Graphical user interface building Algorithm development and modelling
- 4. General Purpose Commands clc , clear ,close all save who , whos cd , ls disp Version Pwd Floor,round,abs date
- 5. ARITHMETIC OPERATORS +:ADD,-:SUB,*:MATRIX MUL,/:MATRIX DIV, .*:ARRAY MUL,./:ARRAY DIV LOGICAL OPERATORS AND &,OR |,NOT~ RELATIONAL OPERATORS <,==,>,<=,>=,~=. BITWISE OPERATORS Bitand ,bitcmp,bitor,bitmax,bitxor, bitset,Bitget,bitshift
- 6. FUNCTIONS PLOT linear plot STEM discrete plot GRID add grid lines XLABEL add X-axis label YLABEL add Y-axis label TITLE add graph title SUBPLOTdivide figure window FIGURE create new figure window PAUSE wait for user response
- 7. GUI FILE&M-FILE IN MATLAB Usually matlab has two file formats they are, M-file Gui –file GUI FILE:A graphical user interface (GUI) is a user interface built with graphical objects, such as buttons, text fields, sliders, and menus. In general, these objects already have meanings to most computer users. M-FILE: It is built with codings,here we use coding to run the programs.
- 8. USER INTERFACE CONTROLS Push Buttons Toggle Buttons Radio Buttons Checkboxes Popup Menus Edit Text Axes Static Text Figures
- 9. IMAGE PROCESSING o Image –It is define as the group of pixels o Image formats o .JPG/.JPEG - Joint Photographic Experts Group o .GIF - Graphics Interchangeable Format o .TIFF - Tagged Image File Format o .PNG - Portable Network Graphics o .BMP - Bitmap format o Applications of image processing o Research o Survillence o Medical
- 10. oPRIMARY COLOURS oSECONDARY COLOURS oCODE CONVERSION
- 11. IMAGE PROCESSING TECHNIQUES oEnhancement o Restoration o Watermarking oCryptography oSteganography oFusion o Retrieval oSegmentation
- 13. WATER MARKING • Water Marking – Embed the secret image in an image or any type of multimedia data. • We should hide the image without changing original image quality. • Water marking is used only for copyright protection • The applications of water marking are, • Tele – broadcasting • Web-applications • There are two types of water marking they are, • Visible water marking • Invisible water marking
- 14. STEGANOGRAPHY o Hiding a Secret data in Digital Images without affecting the quality of Medium. This image is called as StegoImage. Original Image Stego Image Application o Send secret communication like Military applications
- 15. Fusion – Process of Combining two different scanned images to get a single image having more relevant information of those twos Types: Pixel Level Fusion Feature Level Fusion Decision Level Fusion IMAGE FUSION Rule1: Averaging Rule2: Maximum Rule3: Minimum
- 16. SEGMENTATION OUTPUT Cluster1 Cluster2 Cluster3 Cluster4
- 17. TO READ AN IMAGE a =imread('cameraman.tif'); imshow(a); ADD TWO IMAGES I = imread(‘rice.tif'); J = imread('cameraman.tif'); K = imadd(I,J,'uint16'); imshow(K,[])
- 18. CONVERT IMAGE TO GRAY AND BINARY clc; clear; close all a= imread(‘peppers.png'); subplot(2,2,1); imshow(a); subplot(2,2,2); b=imresize(a,[256 256]); imshow(b); subplot(2,2,3); c=rgb2gray(b); imshow(c); subplot(2,2,4); d=im2bw(c); imshow(d);
- 19. RGB COMPONENT a=imread(‘peppers.png’) subplot(2,2,1); imshow(a); [r c p]=size(a) R=a; G=a; B=a; R(:,:,2:3)=0; subplot(2,2,2); imshow(R); G(:,:,1)=0; G(:,:,3)=0; subplot(2,2,3); imshow(G); B(:,:,1)=0; B(:,:,2)=0; subplot(2,2,4); imshow(B);
- 20. a=imread(‘rice.png’); figure; imshow(a); b=imnoise(a,’salt & pepper’,0.02) Figure; Imshow(B); c=medfilt2(b); Figure; Imshow(c) FILTER TO REMOVE THE NOISES