Matlab Workshop Day2_001

8/13/2019 Matlab Workshop Day2_001

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Scripts

User defined sequence of commands. Scripts in matlab are files terminated with a

.m extension( thus called M-files)

M-file : matlab console :: batch files :command prompt

Matlab functions also written as M-files.

To create: File->new->scripts/functions OR

type edit mfilename.m Function syntax- function [output variable

list]=function name(input argument list)


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Some Notes on scripts and

functions Avoid naming mfiles after inbuilt functions or

variable names, it creates problems whilecalling.

Precedence order- variable>nested fn>subfn>current dir fn>inbuilt fn (for those thatwant to know)

While calling a script/function make sure

that your current directory(found by typingpwd) is where you saved your m-file or thatyour script directory is added to the matlabscript path.


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The function declaration must be the first

executable line of any MATLAB function.

For functions the name of the m-file

should be same as the main function

name that is mentioned in the 1stline of

the m-file. For eg. An average function should be

named as avg.m and first line should

contain function out=avg(inp)


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The variables within the body of the

function are all local variables.

Although generally not necessary itsbetter to end a function with an end

statement( it becomes necessary in

nested functions) Write a few lines of comments at the

start of the function body as it appears

when help for the particular function iscalled and maybe useful later.


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An example script

Lets write a script to plot a sinusoidalwaveform.

Open script file and start typing

theta=linspace(0,2*pi,1000);

plot(theta,sin(theta));%where sin() is an inbuilt functionto generate sin values of data in matrices/array

Save and close the script file; type thefilename in the console.


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Functions

Used to perform predefined action on inputdata.

function [out1, out2, ...] = fnname(in1, in2, ...)declares the function fnname, and its inputs

and outputs Subfunctions are functions defined after the

main function in an mfile. They are visible andusable only by the main function or other

subfunctions in the mfile. Functions can be called from the console or

other functions.


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Popular inbuilt functions

In matlab console type help elfun andyoull be given a list of elementary built-in

functions.

Type help specfun for list of specialinbuilt functions.

You can click on the hyperlinks in the help

to see how and where to use each ofthose functions


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Varargin, varargout, nargin, nargout

varargin, varargout used for variableinput/output arguments.

Similar to elipsis in c.

Varargin is a cell ( array of arrays just thatarrays need not be of same dimension)

Nargin and nargout specify the nos. ofinputs and outputs (helps in knowing nosof variable arguments)

Used as function [out1,out2,varargout]=fn(in1,in2,varargin)


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Exercise

Try writing a script to draw a circle. Hint :you have to use sqrt, hold on, axis square functions; sosee help on what they do.

Try writing a function to find mean and

std dev of a sequence. It should havemean and stddev as the 2 outputs and thesequence as an array input.

Try calling the function as fnname(1:10)and later as [mean,stddev]=fnname(1:10)and see the difference.


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Signal processing toolbox

Signal processing toolbox can be used tovisualize signals in time and frequency

domains, compute FFTs for spectral analysis,

design FIR and IIR filters, and implementconvolution, modulation, resampling, and

other signal processing techniques You can

view and measure signals, design digital

filters, and analyze spectral windows.

Overall its a good learning and

developmental tool for signal processing.


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A suite of interactive graphical user

interfaces(GUI)

The signal processing toolbox contains verygood GUIs for the following:

Filter design and analysis

Window design and analysis Signal plotting and analysis

Spectral analysis

Filtering signals


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Since MATLAB is a programming language, an endless variety ofdifferent signals is possible. Here are some statements that generate

several commonly used sequences, including the unit impulse, unit

step, and unit ramp functions:

t = (0:0.01:1);

y = ones(101); % step

y = [1; zeros(100,1)]; % impulse

y = t ; % rampy = t.^2; % exponential

y = square(2*pi*4*t); % generates a square wave every 0.25secs.

Signal Processing BasicsCommon Sequences


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Waveform generat ion

y = sin(2*pi*50*t) + 2*sin(2*pi*120*t); %two sinusoids,%one at 50 Hz%and one at

%120Hz with

%twice the amplitude

plot(t,y) %plot y versus time

plot(t(1:50),y(1:50)) %display only the first

%50 points(zoom!)


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Filter Implementation and AnalysisConvolut ion and Fi lter ing

The mathematical foundation of filtering is convolution. TheMATLAB convfunction performs standard one-dimensionalconvolution, convolving one vector with another

A digital filter's outputy(k) is related to its inputx(k) byconvolution with its impulse response h(k).


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Cont.

x = [1 2 1];

h = [1 1 1];

y = conv(h,x);

stem(y)


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Filters and Transfer Functions

In general, thez-transform Y(z) of a digital filter's outputy(n) is

related to thez-transformX(z) of the input by

where H(z) is the filter's transfer function. Here, the constantsb(i) and a(i) are the filter coefficients and the order of the filteris the maximum of nand m.

H(z)


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Cont.

For example let;

step = ones(50); %input data : step function

b = 1; % Numerator a = [1 -0.9]; % Denominator

where the vectors b and a represent the coefficients of a filter intransfer function form. To apply this filter to your data, use

y = filter(b,a,step);

stem(y)

fvtool(b,a) %GUI.Dont have to define input (if input is%step/impulse function)%

19.01

1)(

zzH


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Images and their toolboxes

All images in stored in computers are digitalimages, ie. they are sampled and quantized.The samples of an image being called a pixel.

Greyscale images are 8bit quantized.

Color images in matlab are commonlyrepresented in 2 methods- rgb and hsv.Overall color images are 3d matrices or 2d

index matrix with a separate colormap. Videos are treated as a collection of many

image frames or sampled in time and space.


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Image acquisition

For loading an image we use the imreadcommand.

Used as img=imread(filename);

Supports a wide range of file formats,type imformats to see supported formats.

Try colimg=imread(autumn.tif); and

grayimg=imread(liftingbody.png);


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To display an image we use

imshow(imgobject);

To convert between various image typeswe use functions like im2bw,

rgb2gray,rgb2ind,ind2rgb,rgb2hsv etc.

Now lets come to actual imageacquisition. For eg. from a camera.

To acquire camera image we use

vidobj=videoinput(adaptorname); For windows, camera input is generally in

winvideo adaptor (videoinput(winvideo))


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To view the camera input use

preview(vidobj)

To get an image from the camera useimg=getsnapshot(vidobj)

To get a video stream from the camera

use vid=getdata(vidobj). Note: nos offrames taken depends on the

FramesPerTrigger property of vidobj.

Use implay(vid) to play the video.


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Image processing toolbox

To view pixel values in the neighborhood ofa point open the image using imshow andtype impixelregion and move the point usingthe cursor.

To crop an image use imcrop function. For interactive crop use

cropimg=imcrop(img) For programmatic crop use

cropimg=imcrop(img,rect); where rect isarray defining rectangle properties as[xmin,ymin,width,height]


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Image can be resized usingnewimg=imresize(old,scale) for aspectlocked scaling or asnewimg=imresize(old,[numrows,numcols]) for general resize.

To rotate an image use

rotimg=imrotate(img,angle); where angleis counter clockwise in degrees.

Imhist(img) is used to display thehistogram of an image. Note: it worksonly on greyscale images or indexed colorimages.


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To increase contrast in an image we can

normalize the histogram using the

functions histeq(img) or imadjust(im) Regionprops function can be used to

obtain properties of regions in an image.

Regionprops can be used for BW orlabeled images only( for BW images it

generates properties of connected

components and for labeled imagesgenerates properties for each label).


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Regionprops is used as

stats=regionprops(img,properties); where

properties is the list of properties youwant.

Properties that can be returned by

regionprops can be viewed in its helpdocumentation.

There are many more interesting

functions in IP toolbox which can bebetter understood after gaining a good

base in IP theory.


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Other toolboxes

Other toolboxes can be easily learnt onceyou have a thorough understanding of theconcepts.

The help documentation in matlab is oneof the best, so use it.

All help documentation containillustrations at the end.

Toolboxes come with demos for a fewfamous applications which can also beviewed in help.

Matlab Workshop Day2_001

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