MGM's Jawaharlal Nehru Engineering College N-6, Cidco, Aurangabad, Maharashtra Department of Instrumentation & Control Engineering

Transcription

1 MGM's Jawaharlal Nehru Engineering College N-6, Cidco, Aurangabad, Maharashtra Department of Instrumentation & Control Engineering Laboratory Manual Digital Signal & Image Processing Third Year: Semester VI Session: Prepared By: Mr. Saurabh Kumar Assistant Professor

2 Experiment no. 1 AIM: - TO write a MATLAB program to common continues time signals ALGORITHM:- 1. Get the amplitude and frequency of the signal 2. Use sin, cos, square matlab built in functions 3. Using plot function plot the signal MATLAB CODE:- Program: MATLAB Result: clc; clear all; close all; t=0:.001:1; f=input('enter the value of frequency'); a=input('enter the value of amplitude'); %Sine wave% subplot(3,3,1); y=a*sin(2*pi*f*t); plot(t,y,'r'); title('sine wave') %Cosine wave% subplot(3,3,2); z=a*cos(2*pi*f*t); plot(t,z); title('cosine wave') %square wave% subplot(3,3,3); s=a*square(2*pi*f*t);

3 plot(t,s); title('square wave') %ramp wave% subplot(3,3,4); plot(t,t); title('ramp wave') %Unit Step Wave% subplot(3,3,5); plot(t,a,'r'); title('unit step wave') SAMPLE INPUT: Enter the value of frequency2 Enter the value of amplitude1 RESULTS:- Thus the generation of continues time signals using matlab was verified.

4 Experiment no. 2 AIM: - TO write a MATLAB program to common discrete time signals ALGORITHM:- 1. Get the amplitude and frequency of the signal 2. Use sin, cos, square matlab built in functions 3. Using stem function plot the signal Program: Result: clc; clear all; close all; n=0:1:50; f=input('enter the value of frequency'); a=input('enter the value of amplitude'); N=input('Enter the length of unit step' ); subplot(3,3,1); y=a*sin(2*pi*f*n); stem(n,y,'r'); title('sine wave') subplot(3,3,2); z=a*cos(2*pi*f*n); stem(n,z); title('cosine wave') subplot(3,3,3); s=a*square(2*pi*f*n); stem(n,s); title('square wave')

5 subplot(3,3,4); stem(n,n); title('ramp wave') x=0:n-1; d=ones(1,n); subplot(3,3,5); stem(x,d,'r'); title('unit step wave') SAMPLE INPUT: Enter the value of frequency 0.03 Enter the value of amplitude 1 Enter the length of unit step 9 RESULTS: Thus the generation of discrete time signals using matlab was verified.

6 Experiment no. 3 Aim: Write a MATLAB program to find the Discrete Time Fourier Transform (DTFT) of the given sequence. MATLAB Program:- % Evaluation of the DTFT clf; % Compute the frequency samples of the DTFT w = -4*pi : 8*pi/511 : 4*pi; num = [2 1]; den = [1-0.6]; h = freqz(num, den, w); % Plot the DTFT subplot(4,1,1) plot(w,real(h)); title('real part of H(e^{j\omega})') xlabel('\omega /\pi'); ylabel('amplitude'); subplot(4,1,2) plot(w,imag(h));grid title('imaginary part of H(e^{j\omega})') xlabel('\omega /\pi'); ylabel('amplitude'); subplot(4,1,3) plot(w,abs(h));grid title('magnitude Spectrum H(e^{j\omega}) ') xlabel('\omega /\pi'); ylabel('amplitude'); subplot(4,1,4) plot(w,angle(h));grid title('phase Spectrum arg[h(e^{j\omega})]') xlabel('\omega /\pi'); ylabel('phase, radians');

7 Result:-

8 Experiment no.- 4 Aim: Write a MATLAB program to plot magnitude response and phase response of digital FIR Filter using Rectangular window. a. Low pass Filter b. High pass Filter c. Bandpass Filter d. Bandstop Filter a. LOW PASS FIR Filter Designing clc; clear all; close all; N=input('Enter the value of N:'); wc=input('enter cutoff frequency:'); h=fir1(n,wc/pi,rectwin(n+1)); freqz(h); Output: Enter the value of N: 5 Enter cutoff frequency: 0.5*pi b. HIGH PASS FIR Filter Designing Result: clc; clear all; close all; N=input('Enter the value of N:'); wc=input('enter cutoff frequency:'); h=fir1(n,wc/pi, high,rectwin(n+1)); freqz(h); Output: Enter the value of N: 28 Enter cutoff frequency: 0.5*pi c. BAND PASS FIR Filter Designing clc; clear all; MATLAB Program:- Result:- Result:-

9 close all; N=input('Enter the value of N:'); wc=input('enter cutoff frequency:'); h=fir1(n,wc/pi,rectwin(n+1)); freqz(h); Output: Enter the value of N: 28 Enter cutoff frequency: [0.3*pi 0.7*pi] d. BAND STOP FIR Filter Designing Result:- clc; clear all; close all; N=input('Enter the value of N:'); wc=input('enter cutoff frequency:'); h=fir1(n,wc/pi, stop,rectwin(n+1)); freqz(h); Output: Enter the value of N: 28 Enter cutoff frequency: [0.2*pi 0.7*pi] Hanning Window: 1. h=fir1(n,wc/pi,hanning(n+1)); - Low Pass FIR Filter 2. h=fir1(n,wc/pi, high,hanning(n+1)); - High Pass FIR Filter 3. h=fir1(n,wc/pi,hanning(n+1)); - Band Pass FIR Filter 4. h=fir1(n,wc/pi, stop, hanning(n+1)); - Band Stop FIR Filter Hamming Window: 1. h=fir1(n,wc/pi,hamming(n+1)); - Low Pass FIR Filter 2. h=fir1(n,wc/pi, high,hamming(n+1)); - High Pass FIR Filter 3. h=fir1(n,wc/pi,hamming(n+1)); - Band Pass FIR Filter 4. h=fir1(n,wc/pi, stop, hamming(n+1)); - Band Stop FIR Filter

10 Experiment no.-5 AIM: To write and execute programs for image arithmetic operations Introduction: Arithmetic operations like image addition, subtraction, multiplication and division is possible. If there is two images I1 and I2 then addition of image can be given by: I(x,y) = I1(x,y) + I2(x,y) Where I(x,y) is resultant image due to addition of two images. X and y are coordinates of image. Image addition is pixel to pixel. Value of pixel should not cross maximum allowed value that is 255 for 8 bit grey scale image. When it exceeds value 255, it should be clipped to 255. To increase overall brightness of the image, we can add some constant value depending on brightness required. In example program we will add value 50 to the image and compare brightness of original and modified image. To decrease brightness of image, we can subtract constant value. In example program, value 100 is subtracted for every pixel. Care should be taken that pixel value should not less than 0 (minus value). Subtract operation can be used to obtain complement (negative) image in which every pixel is subtracted from maximum value i.e. 255 for 8 bit greyscale image. Multiplication operation can be used to mask the image for obtaining region of interest. Black and white mask (binary image) containing 1s and 0s is multiplied with image to get resultant image. To obtain binary image function im2bw() can be used. Multiplication operation can also be used to increase brightness of the image. Division operation results into floating point numbers. So data type required is floating point numbers. It can be converted into integer data type while storing the image. Division can be used to decrease the brightness of the image. It can also used to detect change in image.

11 Program:- clc; close all; I1 = imread('cameraman.tif'); I2 = imread('rice.png'); subplot(2, 2, 1);imshow(I1);title('Original image I1'); subplot(2, 2, 2);imshow(I2);title('Original image I2'); I=I1+I2; % Addition of two images subplot(2, 2, 3);imshow(I);title('Addition of image I1+I2'); I=I1-I2; %Subtraction of two images subplot(2, 2, 4);imshow(I);title('Subtraction of image I1-I2'); figure; subplot(2, 2, 1);imshow(I1);title('Original image I1'); I=I1+50; subplot(2, 2, 2);imshow(I);title('Bright Image I'); I=I1-100; subplot(2, 2, 3);imshow(I);title('Dark Image I');

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13 Experiment no. 6 AIM: Resizing AND Cropping an Image To resize an image, use the imresize function. When you resize an image, you specify the image to be resized and the magnification factor. To enlarge an image, specify a magnification factor greater than 1. To reduce an image, specify a magnification factor between 0 and 1. MATLAB Program:- %the command below increases the size of an image by 1.25 times. I = imread('circuit.tif'); J = imresize(i,1.25); imshow(i) figure imshow(j) MATLAB Program:- %Creates an output image with 100 rows and 150 columns. I = imread('circuit.tif'); J = imresize(i,[ ]); imshow(i) figure, imshow(j) Cropping an Image MATLAB Program:- I = imread('circuit.tif') J = imcrop(i); MATLAB Program:- I = imread('circuit.tif'); J = imcrop(i,[ ]);

14 Experiment no. 7 AIM: To write and execute program for geometric transformation of image. MATLAB Program:- clc close all filename=input('enter File Name :','s'); x=imread(filename); x=rgb2gray(x); subplot(2,2,1); imshow(x); title('orignial Image'); y=imrotate(x,45,'bilinear','crop'); subplot(2,2,2); imshow(y); title('image rotated by 45 degree'); y=imrotate(x,90,'bilinear','crop'); subplot(2,2,3); imshow(y); title('image rotated by 90 degree'); y=imrotate(x,-45,'bilinear','crop'); subplot(2,2,4); imshow(y); title('image rotated by -45 degree');

15 Result:-

16 Experiment no. 7 AIM: To write and execute program for geometric transformation and shearing of image. MATLAB Program:- clc; close all; clear all; x = imread('cameraman.tif'); tform = maketform('affine',[1 0 0;.5 1 0; 0 0 1]); y = imtransform(x,tform); figure; subplot(2,2,1); imshow(x); title('orignial Image'); subplot(2,2,2); imshow(y); title('shear in X direction'); tform = maketform('affine',[ ; 0 1 0; 0 0 1]); y = imtransform(x,tform); subplot(2,2,3); imshow(y); title('shear in Y direction'); tform = maketform('affine',[ ; ; 0 0 1]); y = imtransform(x,tform); subplot(2,2,4); imshow(y); title('shear in X-Y direction');

17 Experiment no. 8 Analyzing Images Tasks:- Step 1: Read Image Step 2: Subtract the Background Image from the Original Image Step 3:Increase the Image Contrast Step 4: Threshold the Image Step 5: Identify Objects in the Image Step 6: Examine One Object Step 7: View All Objects Step 8: Compute Area of Each Object Step 9: Create Histogram of the Area

18 MATLAB Program:- Results:- clc; close all; clear all; I = imread('rice.png'); imshow(i) background = imopen(i,strel('disk',15)); figure, surf(double(background(1:8:end,1:8:end))), zlim([0 255]); set(gca,'ydir','reverse'); I2 = I - background; figure, imshow(i2) I3 = imadjust(i2); figure, imshow(i3); level = graythresh(i3); bw = im2bw(i3,level); bw = bwareaopen(bw, 50); figure, imshow(bw) cc = bwconncomp(bw, 4) cc.numobjects grain = false(size(bw)); grain(cc.pixelidxlist{50}) = true; figure, imshow(grain); labeled = labelmatrix(cc); RGB_label = 'c', 'shuffle'); figure, imshow(rgb_label) graindata = regionprops(cc, 'basic') graindata(50).area grain_areas = [graindata.area]; [min_area, idx] = min(grain_areas) grain = false(size(bw)); grain(cc.pixelidxlist{idx}) = true; figure, imshow(grain); nbins = 20; figure, hist(grain_areas, nbins) title('histogram of Rice Grain Area');