以下6個函式是opencv有關角點檢測的函式 ConerHarris, cornoerMinEigenVal,CornorEigenValsAndVecs, preConerDetect, conerSubPix, goodFeaturesToTracks, 其中， 前三個都呼叫靜態函式cornerEigenValsVecs

1、靜態函式cornerEigenValsVecs;

static void
cornerEigenValsVecs( const Mat& src, Mat& eigenv, int block_size,
                     
 
int aperture_size, int op_type, double k=0.,
                     int borderType=BORDER_DEFAULT )
{
#ifdef HAVE_TEGRA_OPTIMIZATION
    if (tegra::useTegra() && tegra::cornerEigenValsVecs(src, eigenv, block_size, aperture_size, op_type, k, borderType))
        return;
#endif
#if CV_TRY_AVX
    bool
 
 haveAvx = CV_CPU_HAS_SUPPORT_AVX;
#endif
#if CV_SIMD128
    bool haveSimd = hasSIMD128();
#endif

    int depth = src.depth();
    double scale = (double)(1 << ((aperture_size > 0 ? aperture_size : 3) - 1)) * block_size;
    if( aperture_size < 0 )
        scale *= 2.0;
    if( depth == CV_8U )
        scale 
 
*= 255.0;
    scale = 1.0/scale;

    CV_Assert( src.type() == CV_8UC1 || src.type() == CV_32FC1 );

    Mat Dx, Dy;
    if( aperture_size > 0 )
    {
        Sobel( src, Dx, CV_32F, 1, 0, aperture_size, scale, 0, borderType );
        Sobel( src, Dy, CV_32F, 0, 1, aperture_size, scale, 0, borderType );
    }
    else
    {
        Scharr( src, Dx, CV_32F, 1, 0, scale, 0, borderType );
        Scharr( src, Dy, CV_32F, 0, 1, scale, 0, borderType );
    }

    Size size = src.size();
    Mat cov( size, CV_32FC3 );
    int i, j;

    for( i = 0; i < size.height; i++ )
    {
        float* cov_data = cov.ptr<float>(i);
        const float* dxdata = Dx.ptr<float>(i);
        const float* dydata = Dy.ptr<float>(i);

#if CV_TRY_AVX
        if( haveAvx )
            j = cornerEigenValsVecsLine_AVX(dxdata, dydata, cov_data, size.width);
        else
#endif // CV_TRY_AVX
            j = 0;

#if CV_SIMD128
        if( haveSimd )
        {
            for( ; j <= size.width - v_float32x4::nlanes; j += v_float32x4::nlanes )
            {
                v_float32x4 v_dx = v_load(dxdata + j);
                v_float32x4 v_dy = v_load(dydata + j);

                v_float32x4 v_dst0, v_dst1, v_dst2;
                v_dst0 = v_dx * v_dx;
                v_dst1 = v_dx * v_dy;
                v_dst2 = v_dy * v_dy;

                v_store_interleave(cov_data + j * 3, v_dst0, v_dst1, v_dst2);
            }
        }
#endif // CV_SIMD128

        for( ; j < size.width; j++ )
        {
            float dx = dxdata[j];
            float dy = dydata[j];

            cov_data[j*3] = dx*dx;
            cov_data[j*3+1] = dx*dy;
            cov_data[j*3+2] = dy*dy;
        }
    }

    //盒式均值濾波；
    boxFilter(cov, cov, cov.depth(), Size(block_size, block_size),
        Point(-1,-1), false, borderType );

    if( op_type == MINEIGENVAL )
        calcMinEigenVal( cov, eigenv );                    //最小特徵值；  如果最小的特徵值都滿足角點的要求，那麼說明是角點，並且是強角點；
    else if( op_type == HARRIS )
        calcHarris( cov, eigenv, k );
    else if( op_type == EIGENVALSVECS )
        calcEigenValsVecs( cov, eigenv );
}

2、preConerDetect函式分析；

3、cornorSubPix函式分析；

4、goodFeaturesToTrack函式分析；

注： 該博文為擴充套件型；