Adding automatic thresholding to cvCanny in OpenCV

canny.cpp

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#include "precomp.hpp"

CV_IMPL void cvCanny( const void* srcarr, void* dstarr,
                      double low_thresh, double high_thresh,
                      int aperture_size )
{
    cv::Ptr<CvMat> dx, dy;
    cv::AutoBuffer<char> buffer;
    std::vector<uchar*> stack;
    uchar **stack_top = 0, **stack_bottom = 0;

	double percent = low_thresh;

    CvMat srcstub, *src = cvGetMat( srcarr, &srcstub );
    CvMat dststub, *dst = cvGetMat( dstarr, &dststub );
    CvSize size;
    int flags = aperture_size;
    int low, high;
    uchar* map;
    ptrdiff_t mapstep;
    int maxsize;
    int i, j;
    CvMat mag_row;

    if( CV_MAT_TYPE( src->type ) != CV_8UC1 ||
        CV_MAT_TYPE( dst->type ) != CV_8UC1 )
        CV_Error( CV_StsUnsupportedFormat, "" );

    if( !CV_ARE_SIZES_EQ( src, dst ))
        CV_Error( CV_StsUnmatchedSizes, "" );

    if( low_thresh > high_thresh )
    {
        double t;
        CV_SWAP( low_thresh, high_thresh, t );
    }

    aperture_size &= INT_MAX;
    if( (aperture_size & 1) == 0 || aperture_size < 3 || aperture_size > 7 )
        CV_Error( CV_StsBadFlag, "" );

    size = cvGetMatSize( src );

	// convolve with sobel operator to get derivative approximations
    dx = cvCreateMat( size.height, size.width, CV_16SC1 );
    dy = cvCreateMat( size.height, size.width, CV_16SC1 );
    cvSobel( src, dx, 1, 0, aperture_size );
    cvSobel( src, dy, 0, 1, aperture_size );

    if( flags & CV_CANNY_L2_GRADIENT )
    {
        Cv32suf ul, uh;
        ul.f = (float)low_thresh;
        uh.f = (float)high_thresh;

        low = ul.i;
        high = uh.i;
    }
    else
    {
        low = cvFloor( low_thresh );
        high = cvFloor( high_thresh );
    }


	// buffer structure will be: top half for 2d mag array,
	// bottom half for map of edges (either 0, 1, or 2...see below)
    buffer.allocate( (size.width+2)*(size.height+2) + (size.width + 2)*(size.height+2)*sizeof(int) );

	// mag is a pointer to the magnitude array
    int *mag = (int*)(char*)buffer;

	// map is a pointer to the edges array
    map = (uchar*)(mag + (size.width+2)*(size.height+2));
    
	mapstep = size.width + 2;

    maxsize = MAX( 1 << 10, size.width*size.height/10 );
    stack.resize( maxsize );
    stack_top = stack_bottom = &stack[0];

    memset( mag, 0, (size.width + 2) * (size.height + 2) * sizeof(int) );
    memset( map, 1, mapstep );
    memset( map + mapstep*(size.height + 1), 1, mapstep );

    /* sector numbers 
       (Top-Left Origin)

        1   2   3
         *  *  * 
          * * *  
        0*******0
          * * *  
         *  *  * 
        3   2   1
    */

    #define CANNY_PUSH(d)    *(d) = (uchar)2, *stack_top++ = (d)
    #define CANNY_POP(d)     (d) = *--stack_top

    mag_row = cvMat( 1, size.width, CV_32F );
	
	// we actually want to start from (1,1), because there's a 1-cell border
	// around the whole image for padding. 
	mag = mag + size.width + 2 + 1;

    // calculate magnitude and angle of gradient, perform non-maxima supression.
    // fill the map with one of the following values:
    //   0 - the pixel might belong to an edge
    //   1 - the pixel can not belong to an edge
    //   2 - the pixel does belong to an edge
    for( i = 0; i <= size.height; i++ )
    {
		// here we move one column over, b/c the first column is padding.	
		int *_mag = mag + (size.width + 2) * i;
        float* _magf = (float*)_mag;
        const short* _dx = (short*)(dx->data.ptr + dx->step*i);
        const short* _dy = (short*)(dy->data.ptr + dy->step*i);
        int x, y;

        if( i < size.height ) {
            _mag[-1] = _mag[size.width] = 0;

            if( !(flags & CV_CANNY_L2_GRADIENT) ) {
                for( j = 0; j < size.width; j++ ) {
                    _mag[j] = abs(_dx[j]) + abs(_dy[j]);
				}
			}
            else {
                for( j = 0; j < size.width; j++ ) {
                    x = _dx[j]; y = _dy[j];
                    _magf[j] = (float)std::sqrt((double)x*x + (double)y*y);
                }
            }
			
        }
        else
            memset( _mag-1, 0, (size.width + 2)*sizeof(int) );
	}

	// Choose better thresholds
	int max = 0;
	for (i = 0; i < size.height; i++) {
		int *_mag = mag + (size.width + 2) * i;
		for( j = 0; j < size.width; j++ ) {
			if (_mag[j] > max) {
				max = _mag[j];
			}
		}
	}
	
	// step 2: Get the histogram of the data.
#define NUM_BINS 64
	// might want to make this max - min / NUM_BINS after you have normalized.
	int bin_size = max / NUM_BINS;
	if (bin_size < 1) bin_size = 1;
	int bins[NUM_BINS] = { 0 };

	for (i = 0; i < size.height; i++) {
		int *_mag = mag + (size.width + 2) * i;
		for( j = 0; j < size.width; j++ ) {
			bins[_mag[j] / bin_size]++;
		}
	}

	// step 3: get the high threshold
	double percent_of_pixels_not_edges = 0.8;
	double threshold_ratio = 0.4;

	int total = 0;
	high = 0;
	// size.height should be here too, but right now we're going row-by-row
	while (total < size.height * size.width * percent_of_pixels_not_edges) {
		total+= bins[high];
		high++;
	}

	high *= bin_size;
	low = threshold_ratio * high;
	cout << "high: " << high << endl;
	cout << "low: " << low << endl;
	int adit = 10;

	// non-maxima suppression
	
    for( i = 1; i <= size.height; i++ )
    {
		int *_mag = mag + (size.width + 2) * i;
        if( (stack_top - stack_bottom) + size.width > maxsize )
        {
            int sz = (int)(stack_top - stack_bottom);
            maxsize = MAX( maxsize * 3/2, maxsize + 8 );
            stack.resize(maxsize);
            stack_bottom = &stack[0];
            stack_top = stack_bottom + sz;
        }
		const short* _dx = (short*)(dx->data.ptr + dx->step*(i-1));
        const short* _dy = (short*)(dy->data.ptr + dy->step*(i-1));
	    int prev_flag = 0;
		int x, y;

        uchar* _map;
        ptrdiff_t magstep1, magstep2;

        _map = map + mapstep*i + 1;
        _map[-1] = _map[size.width] = 1;

		if (i % 3 == 1) {
			magstep1 = size.width + 2;
			magstep2 = -(size.width + 2);
		} else if (i % 3 == 2) {
			magstep1 = -2 * (size.width + 2);
			magstep2 = -(size.width + 2);
		} else {
			magstep1 =  size.width + 2;
			magstep2 = 2 * (size.width + 2);
		}


        for( j = 0; j < size.width; j++ )
        {
            #define CANNY_SHIFT 15

			// i.e. tan(pi/8) * (1 << CANNY_SHIFT etc...)
            #define TG22  (int)(0.4142135623730950488016887242097*(1<<CANNY_SHIFT) + 0.5)

            x = _dx[j];
            y = _dy[j];

            int s = x ^ y;
            int m = _mag[j];

            x = abs(x);
            y = abs(y);

            if( m > low )
            {
                int tg22x = x * TG22;
                int tg67x = tg22x + ((x + x) << CANNY_SHIFT);

                y <<= CANNY_SHIFT;

                if( y < tg22x )
                {
                    if( m > _mag[j-1] && m >= _mag[j+1] )
                    {
                        if( m > high && !prev_flag && _map[j-mapstep] != 2 )
                        {
                            CANNY_PUSH( _map + j );
                            prev_flag = 1;
                        }
                        else {
                            _map[j] = (uchar)0;
						}
                        continue;
                    }
                }
                else if( y > tg67x )
                {
                    if( m > _mag[j-magstep2] && m >= _mag[j+magstep1] )
                    {
                        if( m > high && !prev_flag && _map[j-mapstep] != 2 )
                        {
                            CANNY_PUSH( _map + j );
                            prev_flag = 1;
                        }
                        else {
                            _map[j] = (uchar)0;
						}							
                        continue;
                    }
                }
                else
                {
                    s = s < 0 ? -1 : 1;
                    if( m > _mag[j+magstep2-s] && m > _mag[j+magstep1+s] )
                    {
                        if( m > high && !prev_flag && _map[j-mapstep] != 2 )
                        {
                            CANNY_PUSH( _map + j );
                            prev_flag = 1;
                        }
                        else {
                            _map[j] = (uchar)0;
						}
                        continue;
                    }
                }
			}
            prev_flag = 0;
            _map[j] = (uchar)1;
		}
	}	
    // now track the edges (hysteresis thresholding)
    while( stack_top > stack_bottom )
    {
        uchar* m;
        if( (stack_top - stack_bottom) + 8 > maxsize )
        {
            int sz = (int)(stack_top - stack_bottom);
            maxsize = MAX( maxsize * 3/2, maxsize + 8 );
            stack.resize(maxsize);
            stack_bottom = &stack[0];
            stack_top = stack_bottom + sz;
        }

        CANNY_POP(m);
    
        if( !m[-1] )
            CANNY_PUSH( m - 1 );
        if( !m[1] )
            CANNY_PUSH( m + 1 );
        if( !m[-mapstep-1] )
            CANNY_PUSH( m - mapstep - 1 );
        if( !m[-mapstep] )
            CANNY_PUSH( m - mapstep );
        if( !m[-mapstep+1] )
            CANNY_PUSH( m - mapstep + 1 );
        if( !m[mapstep-1] )
            CANNY_PUSH( m + mapstep - 1 );
        if( !m[mapstep] )
            CANNY_PUSH( m + mapstep );
        if( !m[mapstep+1] )
            CANNY_PUSH( m + mapstep + 1 );
    }

    // the final pass, form the final image
    for( i = 0; i < size.height; i++ )
    {
        const uchar* _map = map + mapstep*(i+1) + 1;
        uchar* _dst = dst->data.ptr + dst->step*i;
        
        for( j = 0; j < size.width; j++ )
            _dst[j] = (uchar)-(_map[j] >> 1);
    }
	adit = 20;
}

void cv::Canny( const Mat& image, Mat& edges,
                double threshold1, double threshold2,
                int apertureSize, bool L2gradient )
{
    Mat src = image;
    edges.create(src.size(), CV_8U);
    CvMat _src = src, _dst = edges;
    cvCanny( &_src, &_dst, threshold1, threshold2,
        apertureSize + (L2gradient ? CV_CANNY_L2_GRADIENT : 0));
}

/* End of file. */

how do I implement this autodetection file (canny.cpp) and make it detect the edges automatically?

Thanks

csharma2,
You need to download openCV and compile it. Before compiling, replace canny.cpp with this file. Then check out the openCV examples to learn how to detect edges: http://opencv.willowgarage.com/wiki/Welcome/Introduction

Silly question but with the OpenCV 2.1.0, I cant seem to find the canny.cpp file anywhere in any folders! is there a particular folder it is should be located in (or do i need to download a different version of openCV)

Hmm, things could've changed...this fix is pretty old. Sadly the only version I know that definitely works is this one: https://github.com/egonSchiele/OpenCV

could you provide a newer implement with opencv 2.4.5?
i got some problems in compiling with ios
thanks in advance

I don't suppose anyone has implemented this as a free function that doesn't need to be compiled into OpenCV?

Is this the original canny detector?

Is this the original canny detector?

I think this is socall auto-canny