Image Analysis and Computer Vision

How Outliers are Removed?  The matched features between the images have a euclidean distance. Features with euclidean distance beyond the average euclidean or a specified threshold are removed as outliers. SIFT(Lowe, 2004): Detects special features regardless of the scale and orientation of the image, and allows you to reliably detect the same special features even in slightly distorted images, adding noise or changing the lighting and / or viewing point. SIFT detects potentially specific features, and measures the stability of these properties and determines their magnitude by eliminating unstable properties. Then, according to the local gradient direction, for each specific feature, one or more orientations are calculated and assigned. With this information, image data properties can be normalized to scale, position and orientation - so the properties become scalable with respect to these transformations. The method also includes a descriptor, which detects the special pro...

/*Write a function to determine the number of bits you would need to flip to convert from integer A to integer B Input : 29 (11101) & 15 (01111) Output: 2*/ # include<iostream> using namespace std; int main() {     int a,b,c[5],d[5],count,i, bits;     a=29;     b=15;     count=0;   bits=0;         while((a>0) || (b>0))     {     c[count]=a%2;     d[count]=b%2;       a=a/2;     b=b/2;     count=count+1;       if (((a==0) || (a==1)) && ((b==0) || (b==1)))       {         c[count]=a;         d[count]=b;         break;       }        ...