MATLAB (Matrix Laboratory)

image segmentation refers to clustering or grouping of homogeneous pixels into various groups while classification is next hierarchy which labell those clustered pixels as different classes..

●Active Stereo Vision ●Two or more cameras placed at different locations ●One is usually stationery other can be moving ●Passive Stereo Vision

●Two cameras separated by a distance known as base length in the same plane

try dsplpc

yes

Image segmentation is essential for isolating and analyzing specific regions within an image, enabling more accurate interpretation and understanding of visual data. It helps in various applications, such as object detection, medical imaging, and autonomous vehicles, by allowing systems to differentiate between objects and their backgrounds. By segmenting images, algorithms can perform tasks more efficiently, improving performance in areas like classification and recognition. Overall, it enhances the effectiveness of computer vision systems.

A stylised image refers to a representation that emphasizes certain features or characteristics while simplifying or exaggerating others, often to create a specific artistic effect or convey a particular mood. This approach is commonly found in illustrations, animations, and graphic designs, where the artist intentionally departs from realistic depiction to enhance visual impact or express a concept. Stylisation can involve alterations in color, form, and detail, allowing for creative interpretation and expression.

as a general rule of thumb, about 5 times the highest frequency for quality reproduction, although one can sometimes get away with a minimum of 2 times.

7.5KHz

mar ......

Going by your categories, I'd say pixel.

satpal

unbound , integrous, innovative

%the program is developed my Mohendra Roy

%Bioelectronics division, Department of ECE, Tezpur Central University, INDIA,

a=input('Please Give The RANGE : ');

k=-a:+1:+a;

x=input('The input the x: ')

h=input('The input the h: ')

% x=[1 .5 .25]

% h=[1 .5 .25]

f=fliplr(h);

l1=length(x);

l2=length(h);

l3=l1+l2-1;

l4=l2-1;

y=zeros(1,l3);

for p=1:1:l3

p1=p+l4;

h2=zeros(1,l3);

h2([p:p1])=f;

l5=length(h2);

h1=zeros(1,l5);

h1([l2:l3])=x

c1=h1.*h2

c2=0;

for i=1:1:l3

c2=c2+c1([i]);

end

sum=c2

y([p])=sum

end

% temp1=length(x);

% temp2=length(h);

t=length(y);

t2=(t-1)/2;

v=-t2:1:t2;

subplot(3,1,1),stem(k,x,'*');

subplot(3,1,2),stem(k,h,'g*');

subplot(3,1,3),stem(v,y,'r*');

n=input('The lower limit of X axis is: ')

m=input('The Upper limit of X axis is: ')

o=input('The lower limit of Y axis is: ')

p=input('The Upper limit of Y axis is: ')

subplot(3,1,1),stem(k,x,'*');axis([n m o p]);grid on

subplot(3,1,2),stem(k,h,'g*');axis([n m o p]);grid on

subplot(3,1,3),stem(v,y,'r*');axis([n m o p]);grid on

% subplot(3,1,1);stem(x);

% subplot(3,1,2);stem(h);

% subplot(3,1,3);stem(y);

Dark and stormy night

Simulink is a package that is available along with Matlab. But these two are licensed. These can not be downloaded for free.

One can purchase the package.

try yourself

In MATLAB, you can use the prctile function to find percentiles of a dataset. For example, to find the 25th and 75th percentiles of an array data, you would use the following code:

percentiles = prctile(data, [25, 75]);

This will return an array containing the specified percentiles. Make sure that the data variable is a vector or matrix containing the values from which you want to calculate the percentiles.

prewitt filter is kind of edge detection

and almost is better than many kind filter in edge detection

.............

the code in matlab is:

i=imread('cameraman.tif');

edge_p=edge(i,'prewitt');

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