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converted houghlines to C++

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This commit is contained in:
Vadim Pisarevsky 2013-02-12 23:16:06 +04:00
parent 7f8c925319
commit 944588e732
4 changed files with 214 additions and 659 deletions
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1
modules/imgproc/perf/perf_houghLines.cpp
View File

@ -36,5 +36,6 @@ PERF_TEST_P(Image_RhoStep_ThetaStep_Threshold, HoughLines,
TEST_CYCLE() HoughLines(image, lines, rhoStep, thetaStep, threshold);
transpose(lines, lines);
SANITY_CHECK(lines);
}

374
modules/imgproc/src/_list.h
View File

@ -1,374 +0,0 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// Intel License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000, Intel Corporation, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of Intel Corporation may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef _CV_LIST_H_
#define _CV_LIST_H_
#include <stdlib.h>
#include <assert.h>
#define CV_FORCE_INLINE CV_INLINE
#if !defined(_LIST_INLINE)
#define _LIST_INLINE CV_FORCE_INLINE
#endif /*_LIST_INLINE*/
#if defined DECLARE_LIST
#if defined _MSC_VER && _MSC_VER >= 1200
#pragma warning("DECLARE_LIST macro is already defined!")
#endif
#endif /*DECLARE_LIST*/
static const long default_size = 10;
static const long default_inc_size = 10;
struct _pos
{
void* m_pos;
#ifdef _DEBUG
struct _list* m_list;
#endif /*_DEBUG*/
};
typedef struct _pos CVPOS;
struct _list
{
void* m_buffer;
void* m_first_buffer;
long m_buf_size; /* The size of the buffer */
long m_size; /* The number of elements */
CVPOS m_head;
CVPOS m_tail;
CVPOS m_head_free;
};
typedef struct _list _CVLIST;
#define DECLARE_LIST(type, prefix)\
/* Basic element of a list*/\
struct prefix##element_##type\
{\
struct prefix##element_##type* m_prev;\
struct prefix##element_##type* m_next;\
type m_data;\
};\
typedef struct prefix##element_##type ELEMENT_##type;\
/* Initialization and destruction*/\
_LIST_INLINE _CVLIST* prefix##create_list_##type(long);\
_LIST_INLINE void prefix##destroy_list_##type(_CVLIST*);\
/* Access functions*/\
_LIST_INLINE CVPOS prefix##get_head_pos_##type(_CVLIST*);\
_LIST_INLINE CVPOS prefix##get_tail_pos_##type(_CVLIST*);\
_LIST_INLINE type* prefix##get_next_##type(CVPOS*);\
_LIST_INLINE type* prefix##get_prev_##type(CVPOS*);\
_LIST_INLINE int prefix##is_pos_##type(CVPOS pos);\
/* Modification functions*/\
_LIST_INLINE void prefix##clear_list_##type(_CVLIST*);\
_LIST_INLINE CVPOS prefix##add_head_##type(_CVLIST*, type*);\
_LIST_INLINE CVPOS prefix##add_tail_##type(_CVLIST*, type*);\
_LIST_INLINE void prefix##remove_head_##type(_CVLIST*);\
_LIST_INLINE void prefix##remove_tail_##type(_CVLIST*);\
_LIST_INLINE CVPOS prefix##insert_before_##type(_CVLIST*, CVPOS, type*);\
_LIST_INLINE CVPOS prefix##insert_after_##type(_CVLIST*, CVPOS, type*);\
_LIST_INLINE void prefix##remove_at_##type(_CVLIST*, CVPOS);\
_LIST_INLINE void prefix##set_##type(CVPOS, type*);\
_LIST_INLINE type* prefix##get_##type(CVPOS);\
/* Statistics functions*/\
_LIST_INLINE int prefix##get_count_##type(_CVLIST*);
/* This macro finds a space for a new element and puts in into 'element' pointer */
#define INSERT_NEW(element_type, l, element)\
l->m_size++;\
if(l->m_head_free.m_pos != NULL)\
{\
element = (element_type*)(l->m_head_free.m_pos);\
if(element->m_next != NULL)\
{\
element->m_next->m_prev = NULL;\
l->m_head_free.m_pos = element->m_next;\
}\
else\
{\
l->m_head_free.m_pos = NULL;\
}\
}\
else\
{\
if(l->m_buf_size < l->m_size && l->m_head_free.m_pos == NULL)\
{\
*(void**)l->m_buffer = cvAlloc(l->m_buf_size*sizeof(element_type) + sizeof(void*));\
l->m_buffer = *(void**)l->m_buffer;\
*(void**)l->m_buffer = NULL;\
element = (element_type*)((char*)l->m_buffer + sizeof(void*));\
}\
else\
{\
element = (element_type*)((char*)l->m_buffer + sizeof(void*)) + l->m_size - 1;\
}\
}
/* This macro adds 'element' to the list of free elements*/
#define INSERT_FREE(element_type, l, element)\
if(l->m_head_free.m_pos != NULL)\
{\
((element_type*)l->m_head_free.m_pos)->m_prev = element;\
}\
element->m_next = ((element_type*)l->m_head_free.m_pos);\
l->m_head_free.m_pos = element;
/*#define GET_FIRST_FREE(l) ((ELEMENT_##type*)(l->m_head_free.m_pos))*/
#define IMPLEMENT_LIST(type, prefix)\
_CVLIST* prefix##create_list_##type(long size)\
{\
_CVLIST* pl = (_CVLIST*)cvAlloc(sizeof(_CVLIST));\
pl->m_buf_size = size > 0 ? size : default_size;\
pl->m_first_buffer = cvAlloc(pl->m_buf_size*sizeof(ELEMENT_##type) + sizeof(void*));\
pl->m_buffer = pl->m_first_buffer;\
*(void**)pl->m_buffer = NULL;\
pl->m_size = 0;\
pl->m_head.m_pos = NULL;\
pl->m_tail.m_pos = NULL;\
pl->m_head_free.m_pos = NULL;\
return pl;\
}\
void prefix##destroy_list_##type(_CVLIST* l)\
{\
void* cur = l->m_first_buffer;\
void* next;\
while(cur)\
{\
next = *(void**)cur;\
cvFree(&cur);\
cur = next;\
}\
cvFree(&l);\
}\
CVPOS prefix##get_head_pos_##type(_CVLIST* l)\
{\
return l->m_head;\
}\
CVPOS prefix##get_tail_pos_##type(_CVLIST* l)\
{\
return l->m_tail;\
}\
type* prefix##get_next_##type(CVPOS* pos)\
{\
if(pos->m_pos)\
{\
ELEMENT_##type* element = (ELEMENT_##type*)(pos->m_pos);\
pos->m_pos = element->m_next;\
return &element->m_data;\
}\
else\
{\
return NULL;\
}\
}\
type* prefix##get_prev_##type(CVPOS* pos)\
{\
if(pos->m_pos)\
{\
ELEMENT_##type* element = (ELEMENT_##type*)(pos->m_pos);\
pos->m_pos = element->m_prev;\
return &element->m_data;\
}\
else\
{\
return NULL;\
}\
}\
int prefix##is_pos_##type(CVPOS pos)\
{\
return !!pos.m_pos;\
}\
void prefix##clear_list_##type(_CVLIST* l)\
{\
l->m_head.m_pos = NULL;\
l->m_tail.m_pos = NULL;\
l->m_size = 0;\
l->m_head_free.m_pos = NULL;\
}\
CVPOS prefix##add_head_##type(_CVLIST* l, type* data)\
{\
ELEMENT_##type* element;\
INSERT_NEW(ELEMENT_##type, l, element);\
element->m_prev = NULL;\
element->m_next = (ELEMENT_##type*)(l->m_head.m_pos);\
memcpy(&(element->m_data), data, sizeof(*data));\
if(element->m_next)\
{\
element->m_next->m_prev = element;\
}\
else\
{\
l->m_tail.m_pos = element;\
}\
l->m_head.m_pos = element;\
return l->m_head;\
}\
CVPOS prefix##add_tail_##type(_CVLIST* l, type* data)\
{\
ELEMENT_##type* element;\
INSERT_NEW(ELEMENT_##type, l, element);\
element->m_next = NULL;\
element->m_prev = (ELEMENT_##type*)(l->m_tail.m_pos);\
memcpy(&(element->m_data), data, sizeof(*data));\
if(element->m_prev)\
{\
element->m_prev->m_next = element;\
}\
else\
{\
l->m_head.m_pos = element;\
}\
l->m_tail.m_pos = element;\
return l->m_tail;\
}\
void prefix##remove_head_##type(_CVLIST* l)\
{\
ELEMENT_##type* element = ((ELEMENT_##type*)(l->m_head.m_pos));\
if(element->m_next != NULL)\
{\
element->m_next->m_prev = NULL;\
}\
l->m_head.m_pos = element->m_next;\
INSERT_FREE(ELEMENT_##type, l, element);\
l->m_size--;\
}\
void prefix##remove_tail_##type(_CVLIST* l)\
{\
ELEMENT_##type* element = ((ELEMENT_##type*)(l->m_tail.m_pos));\
if(element->m_prev != NULL)\
{\
element->m_prev->m_next = NULL;\
}\
l->m_tail.m_pos = element->m_prev;\
INSERT_FREE(ELEMENT_##type, l, element);\
l->m_size--;\
}\
CVPOS prefix##insert_after_##type(_CVLIST* l, CVPOS pos, type* data)\
{\
ELEMENT_##type* element;\
ELEMENT_##type* before;\
CVPOS newpos;\
INSERT_NEW(ELEMENT_##type, l, element);\
memcpy(&(element->m_data), data, sizeof(*data));\
before = (ELEMENT_##type*)pos.m_pos;\
element->m_prev = before;\
element->m_next = before->m_next;\
before->m_next = element;\
if(element->m_next != NULL)\
element->m_next->m_prev = element;\
else\
l->m_tail.m_pos = element;\
newpos.m_pos = element;\
return newpos;\
}\
CVPOS prefix##insert_before_##type(_CVLIST* l, CVPOS pos, type* data)\
{\
ELEMENT_##type* element;\
ELEMENT_##type* after;\
CVPOS newpos;\
INSERT_NEW(ELEMENT_##type, l, element);\
memcpy(&(element->m_data), data, sizeof(*data));\
after = (ELEMENT_##type*)pos.m_pos;\
element->m_prev = after->m_prev;\
element->m_next = after;\
after->m_prev = element;\
if(element->m_prev != NULL)\
element->m_prev->m_next = element;\
else\
l->m_head.m_pos = element;\
newpos.m_pos = element;\
return newpos;\
}\
void prefix##remove_at_##type(_CVLIST* l, CVPOS pos)\
{\
ELEMENT_##type* element = ((ELEMENT_##type*)pos.m_pos);\
if(element->m_prev != NULL)\
{\
element->m_prev->m_next = element->m_next;\
}\
else\
{\
l->m_head.m_pos = element->m_next;\
}\
if(element->m_next != NULL)\
{\
element->m_next->m_prev = element->m_prev;\
}\
else\
{\
l->m_tail.m_pos = element->m_prev;\
}\
INSERT_FREE(ELEMENT_##type, l, element);\
l->m_size--;\
}\
void prefix##set_##type(CVPOS pos, type* data)\
{\
ELEMENT_##type* element = ((ELEMENT_##type*)(pos.m_pos));\
memcpy(&(element->m_data), data, sizeof(*data));\
}\
type* prefix##get_##type(CVPOS pos)\
{\
ELEMENT_##type* element = ((ELEMENT_##type*)(pos.m_pos));\
return &(element->m_data);\
}\
int prefix##get_count_##type(_CVLIST* list)\
{\
return list->m_size;\
}
#define DECLARE_AND_IMPLEMENT_LIST(type, prefix)\
DECLARE_LIST(type, prefix)\
IMPLEMENT_LIST(type, prefix)
typedef struct __index
{
int value;
float rho, theta;
}
_index;
DECLARE_LIST( _index, h_ )
#endif/*_CV_LIST_H_*/

495
modules/imgproc/src/hough.cpp
View File

@ -40,38 +40,26 @@
//M*/
#include "precomp.hpp"
#include "_list.h"
#define halfPi ((float)(CV_PI*0.5))
#define Pi ((float)CV_PI)
#define a0 0 /*-4.172325e-7f*/ /*(-(float)0x7)/((float)0x1000000); */
#define a1 1.000025f /*((float)0x1922253)/((float)0x1000000)*2/Pi; */
#define a2 -2.652905e-4f /*(-(float)0x2ae6)/((float)0x1000000)*4/(Pi*Pi); */
#define a3 -0.165624f /*(-(float)0xa45511)/((float)0x1000000)*8/(Pi*Pi*Pi); */
#define a4 -1.964532e-3f /*(-(float)0x30fd3)/((float)0x1000000)*16/(Pi*Pi*Pi*Pi); */
#define a5 1.02575e-2f /*((float)0x191cac)/((float)0x1000000)*32/(Pi*Pi*Pi*Pi*Pi); */
#define a6 -9.580378e-4f /*(-(float)0x3af27)/((float)0x1000000)*64/(Pi*Pi*Pi*Pi*Pi*Pi); */
namespace cv
{
#define _sin(x) ((((((a6*(x) + a5)*(x) + a4)*(x) + a3)*(x) + a2)*(x) + a1)*(x) + a0)
#define _cos(x) _sin(halfPi - (x))
/****************************************************************************************\
* Classical Hough Transform *
\****************************************************************************************/
typedef struct CvLinePolar
// Classical Hough Transform
struct LinePolar
{
float rho;
float angle;
}
CvLinePolar;
};
/*=====================================================================================*/
#define hough_cmp_gt(l1,l2) (aux[l1] > aux[l2])
static CV_IMPLEMENT_QSORT_EX( icvHoughSortDescent32s, int, hough_cmp_gt, const int* )
struct hough_cmp_gt
{
hough_cmp_gt(const int* _aux) : aux(_aux) {}
bool operator()(int l1, int l2) const { return aux[l1] > aux[l2]; }
const int* aux;
};
/*
Here image is an input raster;
step is it's step; size characterizes it's ROI;
@ -82,34 +70,27 @@ array of (rho, theta) pairs. linesMax is the buffer size (number of pairs).
Functions return the actual number of found lines.
*/
static void
icvHoughLinesStandard( const CvMat* img, float rho, float theta,
int threshold, CvSeq *lines, int linesMax )
HoughLinesStandard( const Mat& img, float rho, float theta,
int threshold, vector<Vec2f>& lines, int linesMax )
{
cv::AutoBuffer<int> _accum, _sort_buf;
cv::AutoBuffer<float> _tabSin, _tabCos;
const uchar* image;
int step, width, height;
int numangle, numrho;
int total = 0;
int i, j;
float irho = 1 / rho;
double scale;
CV_Assert( CV_IS_MAT(img) && CV_MAT_TYPE(img->type) == CV_8UC1 );
CV_Assert( img.type() == CV_8UC1 );
image = img->data.ptr;
step = img->step;
width = img->cols;
height = img->rows;
const uchar* image = img.data;
int step = (int)img.step;
int width = img.cols;
int height = img.rows;
numangle = cvRound(CV_PI / theta);
numrho = cvRound(((width + height) * 2 + 1) / rho);
int numangle = cvRound(CV_PI / theta);
int numrho = cvRound(((width + height) * 2 + 1) / rho);
_accum.allocate((numangle+2) * (numrho+2));
_sort_buf.allocate(numangle * numrho);
_tabSin.allocate(numangle);
_tabCos.allocate(numangle);
AutoBuffer<int> _accum((numangle+2) * (numrho+2));
AutoBuffer<int> _sort_buf(numangle * numrho);
AutoBuffer<float> _tabSin(numangle);
AutoBuffer<float> _tabCos(numangle);
int *accum = _accum, *sort_buf = _sort_buf;
float *tabSin = _tabSin, *tabCos = _tabCos;
@ -147,122 +128,104 @@ icvHoughLinesStandard( const CvMat* img, float rho, float theta,
}
// stage 3. sort the detected lines by accumulator value
icvHoughSortDescent32s( sort_buf, total, accum );
std::sort( sort_buf, sort_buf + total, hough_cmp_gt(accum));
// stage 4. store the first min(total,linesMax) lines to the output buffer
linesMax = MIN(linesMax, total);
scale = 1./(numrho+2);
double scale = 1./(numrho+2);
for( i = 0; i < linesMax; i++ )
{
CvLinePolar line;
LinePolar line;
int idx = sort_buf[i];
int n = cvFloor(idx*scale) - 1;
int r = idx - (n+1)*(numrho+2) - 1;
line.rho = (r - (numrho - 1)*0.5f) * rho;
line.angle = n * theta;
cvSeqPush( lines, &line );
lines.push_back(Vec2f(line.rho, line.angle));
}
}
/****************************************************************************************\
* Multi-Scale variant of Classical Hough Transform *
\****************************************************************************************/
// Multi-Scale variant of Classical Hough Transform
//DECLARE_AND_IMPLEMENT_LIST( _index, h_ );
IMPLEMENT_LIST( _index, h_ )
static void
icvHoughLinesSDiv( const CvMat* img,
float rho, float theta, int threshold,
int srn, int stn,
CvSeq* lines, int linesMax )
struct hough_index
{
std::vector<uchar> _caccum, _buffer;
std::vector<float> _sinTable;
std::vector<int> _x, _y;
float* sinTable;
int *x, *y;
uchar *caccum, *buffer;
_CVLIST* list = 0;
hough_index() : value(0), rho(0.f), theta(0.f) {}
hough_index(int _val, float _rho, float _theta)
: value(_val), rho(_rho), theta(_theta) {}
int value;
float rho, theta;
};
#define _POINT(row, column)\
(image_src[(row)*step+(column)])
static void
HoughLinesSDiv( const Mat& img,
float rho, float theta, int threshold,
int srn, int stn,
vector<Vec2f>& lines, int linesMax )
{
#define _POINT(row, column)\
(image_src[(row)*step+(column)])
uchar *mcaccum = 0;
int rn, tn; /* number of rho and theta discrete values */
int index, i;
int ri, ti, ti1, ti0;
int row, col;
float r, t; /* Current rho and theta */
float rv; /* Some temporary rho value */
float irho;
float itheta;
float srho, stheta;
float isrho, istheta;
const uchar* image_src;
int w, h, step;
int fn = 0;
float xc, yc;
const float d2r = (float)(Pi / 180);
const float d2r = (float)(CV_PI / 180);
int sfn = srn * stn;
int fi;
int count;
int cmax = 0;
CVPOS pos;
_index *pindex;
_index vi;
vector<hough_index> lst;
CV_Assert( CV_IS_MAT(img) && CV_MAT_TYPE(img->type) == CV_8UC1 );
CV_Assert( img.type() == CV_8UC1 );
CV_Assert( linesMax > 0 && rho > 0 && theta > 0 );
threshold = MIN( threshold, 255 );
image_src = img->data.ptr;
step = img->step;
w = img->cols;
h = img->rows;
const uchar* image_src = img.data;
int step = (int)img.step;
int w = img.cols;
int h = img.rows;
irho = 1 / rho;
itheta = 1 / theta;
srho = rho / srn;
stheta = theta / stn;
isrho = 1 / srho;
istheta = 1 / stheta;
float irho = 1 / rho;
float itheta = 1 / theta;
float srho = rho / srn;
float stheta = theta / stn;
float isrho = 1 / srho;
float istheta = 1 / stheta;
rn = cvFloor( sqrt( (double)w * w + (double)h * h ) * irho );
tn = cvFloor( 2 * Pi * itheta );
int rn = cvFloor( sqrt( (double)w * w + (double)h * h ) * irho );
int tn = cvFloor( 2 * CV_PI * itheta );
list = h_create_list__index( linesMax < 1000 ? linesMax : 1000 );
vi.value = threshold;
vi.rho = -1;
h_add_head__index( list, &vi );
lst.push_back(hough_index(threshold, -1.f, 0.f));
/* Precalculating sin */
_sinTable.resize( 5 * tn * stn );
sinTable = &_sinTable[0];
// Precalculate sin table
vector<float> _sinTable( 5 * tn * stn );
float* sinTable = &_sinTable[0];
for( index = 0; index < 5 * tn * stn; index++ )
sinTable[index] = (float)cos( stheta * index * 0.2f );
_caccum.resize(rn * tn);
caccum = &_caccum[0];
memset( caccum, 0, rn * tn * sizeof( caccum[0] ));
vector<uchar> _caccum(rn * tn, (uchar)0);
uchar* caccum = &_caccum[0];
/* Counting all feature pixels */
// Counting all feature pixels
for( row = 0; row < h; row++ )
for( col = 0; col < w; col++ )
fn += _POINT( row, col ) != 0;
_x.resize(fn);
_y.resize(fn);
x = &_x[0];
y = &_y[0];
vector<int> _x(fn), _y(fn);
int* x = &_x[0], *y = &_y[0];
/* Full Hough Transform (it's accumulator update part) */
// Full Hough Transform (it's accumulator update part)
fi = 0;
for( row = 0; row < h; row++ )
{
@ -275,9 +238,9 @@ icvHoughLinesSDiv( const CvMat* img,
float scale_factor;
int iprev = -1;
float phi, phi1;
float theta_it; /* Value of theta for iterating */
float theta_it; // Value of theta for iterating
/* Remember the feature point */
// Remember the feature point
x[fi] = col;
y[fi] = row;
fi++;
@ -289,18 +252,18 @@ icvHoughLinesSDiv( const CvMat* img,
t = (float) fabs( cvFastArctan( yc, xc ) * d2r );
r = (float) sqrt( (double)xc * xc + (double)yc * yc );
r0 = r * irho;
ti0 = cvFloor( (t + Pi / 2) * itheta );
ti0 = cvFloor( (t + CV_PI*0.5) * itheta );
caccum[ti0]++;
theta_it = rho / r;
theta_it = theta_it < theta ? theta_it : theta;
scale_factor = theta_it * itheta;
halftn = cvFloor( Pi / theta_it );
for( ti1 = 1, phi = theta_it - halfPi, phi1 = (theta_it + t) * itheta;
halftn = cvFloor( CV_PI / theta_it );
for( ti1 = 1, phi = theta_it - (float)(CV_PI*0.5), phi1 = (theta_it + t) * itheta;
ti1 < halftn; ti1++, phi += theta_it, phi1 += scale_factor )
{
rv = r0 * _cos( phi );
rv = r0 * std::cos( phi );
i = cvFloor( rv ) * tn;
i += cvFloor( phi1 );
assert( i >= 0 );
@ -314,28 +277,26 @@ icvHoughLinesSDiv( const CvMat* img,
}
}
/* Starting additional analysis */
// Starting additional analysis
count = 0;
for( ri = 0; ri < rn; ri++ )
{
for( ti = 0; ti < tn; ti++ )
{
if( caccum[ri * tn + ti] > threshold )
{
count++;
}
}
}
if( count * 100 > rn * tn )
{
icvHoughLinesStandard( img, rho, theta, threshold, lines, linesMax );
HoughLinesStandard( img, rho, theta, threshold, lines, linesMax );
return;
}
_buffer.resize(srn * stn + 2);
buffer = &_buffer[0];
mcaccum = buffer + 1;
vector<uchar> _buffer(srn * stn + 2);
uchar* buffer = &_buffer[0];
uchar* mcaccum = buffer + 1;
count = 0;
for( ri = 0; ri < rn; ri++ )
@ -355,18 +316,16 @@ icvHoughLinesSDiv( const CvMat* img,
yc = (float) y[index] + 0.5f;
xc = (float) x[index] + 0.5f;
/* Update the accumulator */
// Update the accumulator
t = (float) fabs( cvFastArctan( yc, xc ) * d2r );
r = (float) sqrt( (double)xc * xc + (double)yc * yc ) * isrho;
ti0 = cvFloor( (t + Pi * 0.5f) * istheta );
ti0 = cvFloor( (t + CV_PI * 0.5) * istheta );
ti2 = (ti * stn - ti0) * 5;
r0 = (float) ri *srn;
for( ti1 = 0 /*, phi = ti*theta - Pi/2 - t */ ; ti1 < stn; ti1++, ti2 += 5
/*phi += stheta */ )
for( ti1 = 0; ti1 < stn; ti1++, ti2 += 5 )
{
/*rv = r*_cos(phi) - r0; */
rv = r * sinTable[(int) (abs( ti2 ))] - r0;
rv = r * sinTable[(int) (std::abs( ti2 ))] - r0;
i = cvFloor( rv ) * stn + ti1;
i = CV_IMAX( i, -1 );
@ -377,75 +336,38 @@ icvHoughLinesSDiv( const CvMat* img,
}
}
/* Find peaks in maccum... */
// Find peaks in maccum...
for( index = 0; index < sfn; index++ )
{
i = 0;
pos = h_get_tail_pos__index( list );
if( h_get_prev__index( &pos )->value < mcaccum[index] )
int pos = (int)(lst.size() - 1);
if( pos < 0 || lst[pos].value < mcaccum[index] )
{
vi.value = mcaccum[index];
vi.rho = index / stn * srho + ri * rho;
vi.theta = index % stn * stheta + ti * theta - halfPi;
while( h_is_pos__index( pos ))
hough_index vi(mcaccum[index],
index / stn * srho + ri * rho,
index % stn * stheta + ti * theta - (float)(CV_PI*0.5));
lst.push_back(vi);
for( ; pos >= 0; pos-- )
{
if( h_get__index( pos )->value > mcaccum[index] )
{
h_insert_after__index( list, pos, &vi );
if( h_get_count__index( list ) > linesMax )
{
h_remove_tail__index( list );
}
if( lst[pos].value > vi.value )
break;
}
h_get_prev__index( &pos );
}
if( !h_is_pos__index( pos ))
{
h_add_head__index( list, &vi );
if( h_get_count__index( list ) > linesMax )
{
h_remove_tail__index( list );
}
lst[pos+1] = lst[pos];
}
lst[pos+1] = vi;
if( (int)lst.size() > linesMax )
lst.pop_back();
}
}
}
}
}
pos = h_get_head_pos__index( list );
if( h_get_count__index( list ) == 1 )
for( size_t i = 0; i < lst.size(); i++ )
{
if( h_get__index( pos )->rho < 0 )
{
h_clear_list__index( list );
}
if( lst[i].rho < 0 )
continue;
lines.push_back(Vec2f(lst[i].rho, lst[i].theta));
}
else
{
while( h_is_pos__index( pos ))
{
CvLinePolar line;
pindex = h_get__index( pos );
if( pindex->rho < 0 )
{
/* This should be the last element... */
h_get_next__index( &pos );
assert( !h_is_pos__index( pos ));
break;
}
line.rho = pindex->rho;
line.angle = pindex->theta;
cvSeqPush( lines, &line );
if( lines->total >= linesMax )
break;
h_get_next__index( &pos );
}
}
h_destroy_list__index(list);
}
@ -454,98 +376,80 @@ icvHoughLinesSDiv( const CvMat* img,
\****************************************************************************************/
static void
icvHoughLinesProbabilistic( CvMat* image,
float rho, float theta, int threshold,
int lineLength, int lineGap,
CvSeq *lines, int linesMax )
HoughLinesProbabilistic( Mat& image,
float rho, float theta, int threshold,
int lineLength, int lineGap,
vector<Vec4i>& lines, int linesMax )
{
cv::Mat accum, mask;
cv::vector<float> trigtab;
cv::MemStorage storage(cvCreateMemStorage(0));
CvSeq* seq;
CvSeqWriter writer;
int width, height;
int numangle, numrho;
float ang;
int r, n, count;
CvPoint pt;
Point pt;
float irho = 1 / rho;
CvRNG rng = cvRNG(-1);
const float* ttab;
uchar* mdata0;
RNG rng((uint64)-1);
CV_Assert( CV_IS_MAT(image) && CV_MAT_TYPE(image->type) == CV_8UC1 );
CV_Assert( image.type() == CV_8UC1 );
width = image->cols;
height = image->rows;
int width = image.cols;
int height = image.rows;
numangle = cvRound(CV_PI / theta);
numrho = cvRound(((width + height) * 2 + 1) / rho);
int numangle = cvRound(CV_PI / theta);
int numrho = cvRound(((width + height) * 2 + 1) / rho);
accum.create( numangle, numrho, CV_32SC1 );
mask.create( height, width, CV_8UC1 );
trigtab.resize(numangle*2);
accum = cv::Scalar(0);
Mat accum = Mat::zeros( numangle, numrho, CV_32SC1 );
Mat mask( height, width, CV_8UC1 );
vector<float> trigtab(numangle*2);
for( ang = 0, n = 0; n < numangle; ang += theta, n++ )
for( int n = 0; n < numangle; n++ )
{
trigtab[n*2] = (float)(cos(ang) * irho);
trigtab[n*2+1] = (float)(sin(ang) * irho);
trigtab[n*2] = (float)(cos(n*theta) * irho);
trigtab[n*2+1] = (float)(sin(n*theta) * irho);
}
ttab = &trigtab[0];
mdata0 = mask.data;
cvStartWriteSeq( CV_32SC2, sizeof(CvSeq), sizeof(CvPoint), storage, &writer );
const float* ttab = &trigtab[0];
uchar* mdata0 = mask.data;
vector<Point> nzloc;
// stage 1. collect non-zero image points
for( pt.y = 0, count = 0; pt.y < height; pt.y++ )
for( pt.y = 0; pt.y < height; pt.y++ )
{
const uchar* data = image->data.ptr + pt.y*image->step;
uchar* mdata = mdata0 + pt.y*width;
const uchar* data = image.ptr(pt.y);
uchar* mdata = mask.ptr(pt.y);
for( pt.x = 0; pt.x < width; pt.x++ )
{
if( data[pt.x] )
{
mdata[pt.x] = (uchar)1;
CV_WRITE_SEQ_ELEM( pt, writer );
nzloc.push_back(pt);
}
else
mdata[pt.x] = 0;
}
}
seq = cvEndWriteSeq( &writer );
count = seq->total;
int count = (int)nzloc.size();
// stage 2. process all the points in random order
for( ; count > 0; count-- )
{
// choose random point out of the remaining ones
int idx = cvRandInt(&rng) % count;
int idx = rng.uniform(0, count);
int max_val = threshold-1, max_n = 0;
CvPoint* point = (CvPoint*)cvGetSeqElem( seq, idx );
CvPoint line_end[2] = {{0,0}, {0,0}};
Point point = nzloc[idx];
Point line_end[2];
float a, b;
int* adata = (int*)accum.data;
int i, j, k, x0, y0, dx0, dy0, xflag;
int i = point.y, j = point.x, k, x0, y0, dx0, dy0, xflag;
int good_line;
const int shift = 16;
i = point->y;
j = point->x;
// "remove" it by overriding it with the last element
*point = *(CvPoint*)cvGetSeqElem( seq, count-1 );
nzloc[idx] = nzloc[count-1];
// check if it has been excluded already (i.e. belongs to some other line)
if( !mdata0[i*width + j] )
continue;
// update accumulator, find the most probable line
for( n = 0; n < numangle; n++, adata += numrho )
for( int n = 0; n < numangle; n++, adata += numrho )
{
r = cvRound( j * ttab[n*2] + i * ttab[n*2+1] );
int r = cvRound( j * ttab[n*2] + i * ttab[n*2+1] );
r += (numrho - 1) / 2;
int val = ++adata[r];
if( max_val < val )
@ -625,8 +529,8 @@ icvHoughLinesProbabilistic( CvMat* image,
}
}
good_line = abs(line_end[1].x - line_end[0].x) >= lineLength ||
abs(line_end[1].y - line_end[0].y) >= lineLength;
good_line = std::abs(line_end[1].x - line_end[0].x) >= lineLength ||
std::abs(line_end[1].y - line_end[0].y) >= lineLength;
for( k = 0; k < 2; k++ )
{
@ -664,9 +568,9 @@ icvHoughLinesProbabilistic( CvMat* image,
if( good_line )
{
adata = (int*)accum.data;
for( n = 0; n < numangle; n++, adata += numrho )
for( int n = 0; n < numangle; n++, adata += numrho )
{
r = cvRound( j1 * ttab[n*2] + i1 * ttab[n*2+1] );
int r = cvRound( j1 * ttab[n*2] + i1 * ttab[n*2+1] );
r += (numrho - 1) / 2;
adata[r]--;
}
@ -681,23 +585,56 @@ icvHoughLinesProbabilistic( CvMat* image,
if( good_line )
{
CvRect lr = { line_end[0].x, line_end[0].y, line_end[1].x, line_end[1].y };
cvSeqPush( lines, &lr );
if( lines->total >= linesMax )
Vec4i lr(line_end[0].x, line_end[0].y, line_end[1].x, line_end[1].y);
lines.push_back(lr);
if( (int)lines.size() >= linesMax )
return;
}
}
}
}
void cv::HoughLines( InputArray _image, OutputArray _lines,
double rho, double theta, int threshold,
double srn, double stn )
{
Mat image = _image.getMat();
vector<Vec2f> lines;
if( srn == 0 && stn == 0 )
HoughLinesStandard(image, rho, theta, threshold, lines, INT_MAX);
else
HoughLinesSDiv(image, rho, theta, threshold, srn, stn, lines, INT_MAX);
Mat(lines).copyTo(_lines);
}
void cv::HoughLinesP(InputArray _image, OutputArray _lines,
double rho, double theta, int threshold,
double minLineLength, double maxGap )
{
Mat image = _image.getMat();
vector<Vec4i> lines;
HoughLinesProbabilistic(image, rho, theta, threshold, minLineLength, maxGap, lines, INT_MAX);
Mat(lines).copyTo(_lines);
}
/* Wrapper function for standard hough transform */
CV_IMPL CvSeq*
cvHoughLines2( CvArr* src_image, void* lineStorage, int method,
double rho, double theta, int threshold,
double param1, double param2 )
{
cv::Mat image = cv::cvarrToMat(src_image);
std::vector<cv::Vec2f> l2;
std::vector<cv::Vec4i> l4;
CvSeq* result = 0;
CvMat stub, *img = (CvMat*)src_image;
CvMat* mat = 0;
CvSeq* lines = 0;
CvSeq lines_header;
@ -706,11 +643,6 @@ cvHoughLines2( CvArr* src_image, void* lineStorage, int method,
int linesMax = INT_MAX;
int iparam1, iparam2;
img = cvGetMat( img, &stub );
if( !CV_IS_MASK_ARR(img))
CV_Error( CV_StsBadArg, "The source image must be 8-bit, single-channel" );
if( !lineStorage )
CV_Error( CV_StsNullPtr, "NULL destination" );
@ -758,31 +690,49 @@ cvHoughLines2( CvArr* src_image, void* lineStorage, int method,
switch( method )
{
case CV_HOUGH_STANDARD:
icvHoughLinesStandard( img, (float)rho,
(float)theta, threshold, lines, linesMax );
break;
HoughLinesStandard( image, (float)rho,
(float)theta, threshold, l2, linesMax );
break;
case CV_HOUGH_MULTI_SCALE:
icvHoughLinesSDiv( img, (float)rho, (float)theta,
threshold, iparam1, iparam2, lines, linesMax );
break;
HoughLinesSDiv( image, (float)rho, (float)theta,
threshold, iparam1, iparam2, l2, linesMax );
break;
case CV_HOUGH_PROBABILISTIC:
icvHoughLinesProbabilistic( img, (float)rho, (float)theta,
threshold, iparam1, iparam2, lines, linesMax );
break;
HoughLinesProbabilistic( image, (float)rho, (float)theta,
threshold, iparam1, iparam2, l4, linesMax );
break;
default:
CV_Error( CV_StsBadArg, "Unrecognized method id" );
}
int nlines = (int)(l2.size() + l4.size());
if( mat )
{
if( mat->cols > mat->rows )
mat->cols = lines->total;
mat->cols = nlines;
else
mat->rows = lines->total;
mat->rows = nlines;
}
else
result = lines;
if( nlines )
{
cv::Mat lx = method == CV_HOUGH_STANDARD || method == CV_HOUGH_MULTI_SCALE ?
cv::Mat(nlines, 1, CV_32FC2, &l2[0]) : cv::Mat(nlines, 1, CV_32SC4, &l4[0]);
if( mat )
{
cv::Mat dst(nlines, 1, lx.type(), mat->data.ptr);
lx.copyTo(dst);
}
else
{
cvSeqPushMulti(lines, lx.data, nlines);
}
}
if( !mat )
result = lines;
return result;
}
@ -909,7 +859,7 @@ icvHoughCirclesGradient( CvMat* img, float dp, float min_dist,
sort_buf.resize( MAX(center_count,nz_count) );
cvCvtSeqToArray( centers, &sort_buf[0] );
icvHoughSortDescent32s( &sort_buf[0], center_count, adata );
std::sort(sort_buf.begin(), sort_buf.begin() + center_count, cv::hough_cmp_gt(adata));
cvClearSeq( centers );
cvSeqPushMulti( centers, &sort_buf[0], center_count );
@ -963,7 +913,7 @@ icvHoughCirclesGradient( CvMat* img, float dp, float min_dist,
continue;
dist_buf->cols = nz_count1;
cvPow( dist_buf, dist_buf, 0.5 );
icvHoughSortDescent32s( &sort_buf[0], nz_count1, (int*)ddata );
std::sort(sort_buf.begin(), sort_buf.begin() + nz_count1, cv::hough_cmp_gt((int*)ddata));
dist_sum = start_dist = ddata[sort_buf[nz_count1-1]];
for( j = nz_count1 - 2; j >= 0; j-- )
@ -1102,31 +1052,6 @@ static void seqToMat(const CvSeq* seq, OutputArray _arr)
}
void cv::HoughLines( InputArray _image, OutputArray _lines,
double rho, double theta, int threshold,
double srn, double stn )
{
Ptr<CvMemStorage> storage = cvCreateMemStorage(STORAGE_SIZE);
Mat image = _image.getMat();
CvMat c_image = image;
CvSeq* seq = cvHoughLines2( &c_image, storage, srn == 0 && stn == 0 ?
CV_HOUGH_STANDARD : CV_HOUGH_MULTI_SCALE,
rho, theta, threshold, srn, stn );
seqToMat(seq, _lines);
}
void cv::HoughLinesP( InputArray _image, OutputArray _lines,
double rho, double theta, int threshold,
double minLineLength, double maxGap )
{
Ptr<CvMemStorage> storage = cvCreateMemStorage(STORAGE_SIZE);
Mat image = _image.getMat();
CvMat c_image = image;
CvSeq* seq = cvHoughLines2( &c_image, storage, CV_HOUGH_PROBABILISTIC,
rho, theta, threshold, minLineLength, maxGap );
seqToMat(seq, _lines);
}
void cv::HoughCircles( InputArray _image, OutputArray _circles,
int method, double dp, double min_dist,
double param1, double param2,

3
modules/imgproc/test/test_houghLines.cpp
View File

@ -134,6 +134,9 @@ void CV_HoughLinesTest::run_test(int type)
read( fs["exp_lines"], exp_lines, Mat() );
fs.release();
if( exp_lines.size != lines.size )
transpose(lines, lines);
if ( exp_lines.size != lines.size || norm(exp_lines, lines, NORM_INF) > 1e-4 )
{
ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);