Figure 1: An image — an array or a matrix of pixels arranged in columns and rows.
In a (8-bit) greyscale image each picture element has an assigned intensity that
ranges from 0 to 255. A grey scale image is what people normally call a black and
white image, but the name emphasizes that such an image will also include many
shades of grey.
Figure 2: Each pixel has a value from 0 (black) to 255 (white). The possible range of the pixel
values depend on the colour depth of the image, here 8 bit = 256 tones or greyscales.
A normal greyscale image has 8 bit colour depth = 256 greyscales. A “true colour”
image has 24 bit colour depth = 8 x 8 x 8 bits = 256 x 256 x 256 colours = ~16
million colours.
Answer:
C++ code explained below
Explanation:
#include<bits/stdc++.h>
#include <iostream>
using namespace std;
int FiboNR(int n)
{
int max=n+1;
int F[max];
F[0]=0;F[1]=1;
for(int i=2;i<=n;i++)
{
F[i]=F[i-1]+F[i-2];
}
return (F[n]);
}
int FiboR(int n)
{
if(n==0||n==1)
return n;
else
return (FiboR(n-1)+FiboR(n-2));
}
int main()
{
long long int i,f;
double t1,t2;
int n[]={1,5,10,15,20,25,30,35,40,45,50,55,60,65,70,75};
cout<<"Fibonacci time analysis ( recursive vs. non-recursive "<<endl;
cout<<"Integer FiboR(seconds) FiboNR(seconds) Fibo-value"<<endl;
for(i=0;i<16;i++)
{
clock_t begin = clock();
f=FiboR(n[i]);
clock_t end = clock();
t1=double(end-begin); // elapsed time in milli secons
begin = clock();
f=FiboNR(n[i]);
end = clock();
t2=double(end-begin);
cout<<n[i]<<" "<<t1*1.0/CLOCKS_PER_SEC <<" "<<t2*1.0/CLOCKS_PER_SEC <<" "<<f<<endl; //elapsed time in seconds
}
return 0;
}
Answer:
Hash.
Explanation:
An authentication can be defined as the process of verifying the identity of an individual or electronic device. Authentication work based on the principle (framework) of matching an incoming request from a user or electronic device to a set of uniquely defined credentials.
Basically, authentication ensures a user is truly who he or she claims to be, as well as confirm that an electronic device is valid through the process of verification. Smart cards, digital certificates, picture passwords, and biometrics are generally used to perform an authentication in the field of computer.
Hence, when authenticating a user's password, the password supplied by the user is authenticated by comparing the hash of the password with the one stored on the system.
In Computer science, a hash function can be defined as any function which is used to map data by accepting a block of data with variable length size or arbitrary size as input to produce a fixed size hash values or codes.
Generally, when a block of data (input) of arbitrary size is hashed, the resulting hash values or codes is usually smaller than the input data. Thus, hash functions are considered to be a compression of data and as a result, sometimes called compression functions. Basically, the block size of a hash function typically ranges from 128 bits to 512 bits.
Answer:
6 address lines
Explanation:
The computation of the number of address lines needed is shown below:
Given that
Total memory = 64MB
= 
=
Also we know that in 1MB RAM the number of chips is 6
So, the number of address lines is 
i..e 26 address lines
And, the size of one chip is equivalent to 1 MB i.e. 
For a single 1MB chips of RAM, the number of address lines is
Therefore 6 address lines needed
Answer:
Boundary folding method is basically used in the java algorithm and in the hash table. In the hash function, the left and the right value are basically folded in the fixed boundary between the given center values by using the boundary folding methods.
There are basically two types of folding method in the hashing that are:
- Folding shift
- Folding boundary
In the folding boundary method the outside value are get reversed and the alternate values are get flipped at the boundary folding method.
