Corner detection is an approach used within computer vision systems to extract certain kinds of features and infer the contents of an image. Corner detection is frequently used in motion detection, image registration, video tracking, image mosaicing, panorama stitching, 3D modelling and object recognition. This document describes an algorithm for harris corner detector.

1. File: /home/michel/Desktop/harris.cxx
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//Signature: HarrisDetectorFilter(MyStandardImage& Img, MyHarrisResponseMetric* metric, unsigned int ws)
// Computing luminance image
MyStandardImage ImgGrayA = RGBtoYUVLuminance(Img);
// Computing sobel gradients for the images
MyStandardImage ImgGraySobelX = SobelX(ImgGrayA);
MyStandardImage ImgGraySobelY = SobelY(ImgGrayA);
// Computing derivatives
MyStandardImage ImgAx2 =
MyStandardImage ImgAy2 =
MyStandardImage ImgAxy =
products for images
ImgGraySobelX*ImgGraySobelX; // Ix2
ImgGraySobelY*ImgGraySobelY; // Iy2
ImgGraySobelX*ImgGraySobelY; // Ixy
// Computing blurred images
ImgAx2 = GaussianBlur(ImgAx2, ws);
ImgAy2 = GaussianBlur(ImgAy2, ws);
ImgAxy = GaussianBlur(ImgAxy, ws);
// Computing response R for each image pixel.
unsigned int _rows = Img.rows();
unsigned int _cols = Img.cols();
MyStandardImage TmpImg = MyStandardImage(_rows, _cols);
for (unsigned int i = 0; i < _rows; i++)
{
for(unsigned int j = 0; j < _cols; j++)
{
// Computing the trace and determinante of the matrix
double determinant = ImgAx2(i,j).r()*ImgAy2(i,j).r() - ImgAxy(i, j).r()*ImgAxy(i, j).r();
double trace
= ImgAx2(i,j).r() + ImgAy2(i,j).r();
// Calculating the response Harris R
double R = metric->operator()(determinant, trace);
TmpImg(i, j) = MyStandardPixel(R, R, R);
}
}
// Returning resultant not normalized image
return TmpImg;