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42 #include "precomp.hpp"
43 
44 namespace cv
45 {
46 
47 static const int DIST_SHIFT = 16;
48 static const int INIT_DIST0 = (INT_MAX >> 2);
49 #define  CV_FLT_TO_FIX(x,n)  cvRound((x)*(1<<(n)))
50 
51 static void
initTopBottom(Mat & temp,int border)52 initTopBottom( Mat& temp, int border )
53 {
54     Size size = temp.size();
55     for( int i = 0; i < border; i++ )
56     {
57         int* ttop = temp.ptr<int>(i);
58         int* tbottom = temp.ptr<int>(size.height - i - 1);
59 
60         for( int j = 0; j < size.width; j++ )
61         {
62             ttop[j] = INIT_DIST0;
63             tbottom[j] = INIT_DIST0;
64         }
65     }
66 }
67 
68 
69 static void
distanceTransform_3x3(const Mat & _src,Mat & _temp,Mat & _dist,const float * metrics)70 distanceTransform_3x3( const Mat& _src, Mat& _temp, Mat& _dist, const float* metrics )
71 {
72     const int BORDER = 1;
73     int i, j;
74     const int HV_DIST = CV_FLT_TO_FIX( metrics[0], DIST_SHIFT );
75     const int DIAG_DIST = CV_FLT_TO_FIX( metrics[1], DIST_SHIFT );
76     const float scale = 1.f/(1 << DIST_SHIFT);
77 
78     const uchar* src = _src.ptr();
79     int* temp = _temp.ptr<int>();
80     float* dist = _dist.ptr<float>();
81     int srcstep = (int)(_src.step/sizeof(src[0]));
82     int step = (int)(_temp.step/sizeof(temp[0]));
83     int dststep = (int)(_dist.step/sizeof(dist[0]));
84     Size size = _src.size();
85 
86     initTopBottom( _temp, BORDER );
87 
88     // forward pass
89     for( i = 0; i < size.height; i++ )
90     {
91         const uchar* s = src + i*srcstep;
92         int* tmp = (int*)(temp + (i+BORDER)*step) + BORDER;
93 
94         for( j = 0; j < BORDER; j++ )
95             tmp[-j-1] = tmp[size.width + j] = INIT_DIST0;
96 
97         for( j = 0; j < size.width; j++ )
98         {
99             if( !s[j] )
100                 tmp[j] = 0;
101             else
102             {
103                 int t0 = tmp[j-step-1] + DIAG_DIST;
104                 int t = tmp[j-step] + HV_DIST;
105                 if( t0 > t ) t0 = t;
106                 t = tmp[j-step+1] + DIAG_DIST;
107                 if( t0 > t ) t0 = t;
108                 t = tmp[j-1] + HV_DIST;
109                 if( t0 > t ) t0 = t;
110                 tmp[j] = t0;
111             }
112         }
113     }
114 
115     // backward pass
116     for( i = size.height - 1; i >= 0; i-- )
117     {
118         float* d = (float*)(dist + i*dststep);
119         int* tmp = (int*)(temp + (i+BORDER)*step) + BORDER;
120 
121         for( j = size.width - 1; j >= 0; j-- )
122         {
123             int t0 = tmp[j];
124             if( t0 > HV_DIST )
125             {
126                 int t = tmp[j+step+1] + DIAG_DIST;
127                 if( t0 > t ) t0 = t;
128                 t = tmp[j+step] + HV_DIST;
129                 if( t0 > t ) t0 = t;
130                 t = tmp[j+step-1] + DIAG_DIST;
131                 if( t0 > t ) t0 = t;
132                 t = tmp[j+1] + HV_DIST;
133                 if( t0 > t ) t0 = t;
134                 tmp[j] = t0;
135             }
136             d[j] = (float)(t0 * scale);
137         }
138     }
139 }
140 
141 
142 static void
distanceTransform_5x5(const Mat & _src,Mat & _temp,Mat & _dist,const float * metrics)143 distanceTransform_5x5( const Mat& _src, Mat& _temp, Mat& _dist, const float* metrics )
144 {
145     const int BORDER = 2;
146     int i, j;
147     const int HV_DIST = CV_FLT_TO_FIX( metrics[0], DIST_SHIFT );
148     const int DIAG_DIST = CV_FLT_TO_FIX( metrics[1], DIST_SHIFT );
149     const int LONG_DIST = CV_FLT_TO_FIX( metrics[2], DIST_SHIFT );
150     const float scale = 1.f/(1 << DIST_SHIFT);
151 
152     const uchar* src = _src.ptr();
153     int* temp = _temp.ptr<int>();
154     float* dist = _dist.ptr<float>();
155     int srcstep = (int)(_src.step/sizeof(src[0]));
156     int step = (int)(_temp.step/sizeof(temp[0]));
157     int dststep = (int)(_dist.step/sizeof(dist[0]));
158     Size size = _src.size();
159 
160     initTopBottom( _temp, BORDER );
161 
162     // forward pass
163     for( i = 0; i < size.height; i++ )
164     {
165         const uchar* s = src + i*srcstep;
166         int* tmp = (int*)(temp + (i+BORDER)*step) + BORDER;
167 
168         for( j = 0; j < BORDER; j++ )
169             tmp[-j-1] = tmp[size.width + j] = INIT_DIST0;
170 
171         for( j = 0; j < size.width; j++ )
172         {
173             if( !s[j] )
174                 tmp[j] = 0;
175             else
176             {
177                 int t0 = tmp[j-step*2-1] + LONG_DIST;
178                 int t = tmp[j-step*2+1] + LONG_DIST;
179                 if( t0 > t ) t0 = t;
180                 t = tmp[j-step-2] + LONG_DIST;
181                 if( t0 > t ) t0 = t;
182                 t = tmp[j-step-1] + DIAG_DIST;
183                 if( t0 > t ) t0 = t;
184                 t = tmp[j-step] + HV_DIST;
185                 if( t0 > t ) t0 = t;
186                 t = tmp[j-step+1] + DIAG_DIST;
187                 if( t0 > t ) t0 = t;
188                 t = tmp[j-step+2] + LONG_DIST;
189                 if( t0 > t ) t0 = t;
190                 t = tmp[j-1] + HV_DIST;
191                 if( t0 > t ) t0 = t;
192                 tmp[j] = t0;
193             }
194         }
195     }
196 
197     // backward pass
198     for( i = size.height - 1; i >= 0; i-- )
199     {
200         float* d = (float*)(dist + i*dststep);
201         int* tmp = (int*)(temp + (i+BORDER)*step) + BORDER;
202 
203         for( j = size.width - 1; j >= 0; j-- )
204         {
205             int t0 = tmp[j];
206             if( t0 > HV_DIST )
207             {
208                 int t = tmp[j+step*2+1] + LONG_DIST;
209                 if( t0 > t ) t0 = t;
210                 t = tmp[j+step*2-1] + LONG_DIST;
211                 if( t0 > t ) t0 = t;
212                 t = tmp[j+step+2] + LONG_DIST;
213                 if( t0 > t ) t0 = t;
214                 t = tmp[j+step+1] + DIAG_DIST;
215                 if( t0 > t ) t0 = t;
216                 t = tmp[j+step] + HV_DIST;
217                 if( t0 > t ) t0 = t;
218                 t = tmp[j+step-1] + DIAG_DIST;
219                 if( t0 > t ) t0 = t;
220                 t = tmp[j+step-2] + LONG_DIST;
221                 if( t0 > t ) t0 = t;
222                 t = tmp[j+1] + HV_DIST;
223                 if( t0 > t ) t0 = t;
224                 tmp[j] = t0;
225             }
226             d[j] = (float)(t0 * scale);
227         }
228     }
229 }
230 
231 
232 static void
distanceTransformEx_5x5(const Mat & _src,Mat & _temp,Mat & _dist,Mat & _labels,const float * metrics)233 distanceTransformEx_5x5( const Mat& _src, Mat& _temp, Mat& _dist, Mat& _labels, const float* metrics )
234 {
235     const int BORDER = 2;
236 
237     int i, j;
238     const int HV_DIST = CV_FLT_TO_FIX( metrics[0], DIST_SHIFT );
239     const int DIAG_DIST = CV_FLT_TO_FIX( metrics[1], DIST_SHIFT );
240     const int LONG_DIST = CV_FLT_TO_FIX( metrics[2], DIST_SHIFT );
241     const float scale = 1.f/(1 << DIST_SHIFT);
242 
243     const uchar* src = _src.ptr();
244     int* temp = _temp.ptr<int>();
245     float* dist = _dist.ptr<float>();
246     int* labels = _labels.ptr<int>();
247     int srcstep = (int)(_src.step/sizeof(src[0]));
248     int step = (int)(_temp.step/sizeof(temp[0]));
249     int dststep = (int)(_dist.step/sizeof(dist[0]));
250     int lstep = (int)(_labels.step/sizeof(dist[0]));
251     Size size = _src.size();
252 
253     initTopBottom( _temp, BORDER );
254 
255     // forward pass
256     for( i = 0; i < size.height; i++ )
257     {
258         const uchar* s = src + i*srcstep;
259         int* tmp = (int*)(temp + (i+BORDER)*step) + BORDER;
260         int* lls = (int*)(labels + i*lstep);
261 
262         for( j = 0; j < BORDER; j++ )
263             tmp[-j-1] = tmp[size.width + j] = INIT_DIST0;
264 
265         for( j = 0; j < size.width; j++ )
266         {
267             if( !s[j] )
268             {
269                 tmp[j] = 0;
270                 //assert( lls[j] != 0 );
271             }
272             else
273             {
274                 int t0 = INIT_DIST0, t;
275                 int l0 = 0;
276 
277                 t = tmp[j-step*2-1] + LONG_DIST;
278                 if( t0 > t )
279                 {
280                     t0 = t;
281                     l0 = lls[j-lstep*2-1];
282                 }
283                 t = tmp[j-step*2+1] + LONG_DIST;
284                 if( t0 > t )
285                 {
286                     t0 = t;
287                     l0 = lls[j-lstep*2+1];
288                 }
289                 t = tmp[j-step-2] + LONG_DIST;
290                 if( t0 > t )
291                 {
292                     t0 = t;
293                     l0 = lls[j-lstep-2];
294                 }
295                 t = tmp[j-step-1] + DIAG_DIST;
296                 if( t0 > t )
297                 {
298                     t0 = t;
299                     l0 = lls[j-lstep-1];
300                 }
301                 t = tmp[j-step] + HV_DIST;
302                 if( t0 > t )
303                 {
304                     t0 = t;
305                     l0 = lls[j-lstep];
306                 }
307                 t = tmp[j-step+1] + DIAG_DIST;
308                 if( t0 > t )
309                 {
310                     t0 = t;
311                     l0 = lls[j-lstep+1];
312                 }
313                 t = tmp[j-step+2] + LONG_DIST;
314                 if( t0 > t )
315                 {
316                     t0 = t;
317                     l0 = lls[j-lstep+2];
318                 }
319                 t = tmp[j-1] + HV_DIST;
320                 if( t0 > t )
321                 {
322                     t0 = t;
323                     l0 = lls[j-1];
324                 }
325 
326                 tmp[j] = t0;
327                 lls[j] = l0;
328             }
329         }
330     }
331 
332     // backward pass
333     for( i = size.height - 1; i >= 0; i-- )
334     {
335         float* d = (float*)(dist + i*dststep);
336         int* tmp = (int*)(temp + (i+BORDER)*step) + BORDER;
337         int* lls = (int*)(labels + i*lstep);
338 
339         for( j = size.width - 1; j >= 0; j-- )
340         {
341             int t0 = tmp[j];
342             int l0 = lls[j];
343             if( t0 > HV_DIST )
344             {
345                 int t = tmp[j+step*2+1] + LONG_DIST;
346                 if( t0 > t )
347                 {
348                     t0 = t;
349                     l0 = lls[j+lstep*2+1];
350                 }
351                 t = tmp[j+step*2-1] + LONG_DIST;
352                 if( t0 > t )
353                 {
354                     t0 = t;
355                     l0 = lls[j+lstep*2-1];
356                 }
357                 t = tmp[j+step+2] + LONG_DIST;
358                 if( t0 > t )
359                 {
360                     t0 = t;
361                     l0 = lls[j+lstep+2];
362                 }
363                 t = tmp[j+step+1] + DIAG_DIST;
364                 if( t0 > t )
365                 {
366                     t0 = t;
367                     l0 = lls[j+lstep+1];
368                 }
369                 t = tmp[j+step] + HV_DIST;
370                 if( t0 > t )
371                 {
372                     t0 = t;
373                     l0 = lls[j+lstep];
374                 }
375                 t = tmp[j+step-1] + DIAG_DIST;
376                 if( t0 > t )
377                 {
378                     t0 = t;
379                     l0 = lls[j+lstep-1];
380                 }
381                 t = tmp[j+step-2] + LONG_DIST;
382                 if( t0 > t )
383                 {
384                     t0 = t;
385                     l0 = lls[j+lstep-2];
386                 }
387                 t = tmp[j+1] + HV_DIST;
388                 if( t0 > t )
389                 {
390                     t0 = t;
391                     l0 = lls[j+1];
392                 }
393                 tmp[j] = t0;
394                 lls[j] = l0;
395             }
396             d[j] = (float)(t0 * scale);
397         }
398     }
399 }
400 
401 
getDistanceTransformMask(int maskType,float * metrics)402 static void getDistanceTransformMask( int maskType, float *metrics )
403 {
404     CV_Assert( metrics != 0 );
405 
406     switch (maskType)
407     {
408     case 30:
409         metrics[0] = 1.0f;
410         metrics[1] = 1.0f;
411         break;
412 
413     case 31:
414         metrics[0] = 1.0f;
415         metrics[1] = 2.0f;
416         break;
417 
418     case 32:
419         metrics[0] = 0.955f;
420         metrics[1] = 1.3693f;
421         break;
422 
423     case 50:
424         metrics[0] = 1.0f;
425         metrics[1] = 1.0f;
426         metrics[2] = 2.0f;
427         break;
428 
429     case 51:
430         metrics[0] = 1.0f;
431         metrics[1] = 2.0f;
432         metrics[2] = 3.0f;
433         break;
434 
435     case 52:
436         metrics[0] = 1.0f;
437         metrics[1] = 1.4f;
438         metrics[2] = 2.1969f;
439         break;
440     default:
441         CV_Error(CV_StsBadArg, "Uknown metric type");
442     }
443 }
444 
445 struct DTColumnInvoker : ParallelLoopBody
446 {
DTColumnInvokercv::DTColumnInvoker447     DTColumnInvoker( const Mat* _src, Mat* _dst, const int* _sat_tab, const float* _sqr_tab)
448     {
449         src = _src;
450         dst = _dst;
451         sat_tab = _sat_tab + src->rows*2 + 1;
452         sqr_tab = _sqr_tab;
453     }
454 
operator ()cv::DTColumnInvoker455     void operator()( const Range& range ) const
456     {
457         int i, i1 = range.start, i2 = range.end;
458         int m = src->rows;
459         size_t sstep = src->step, dstep = dst->step/sizeof(float);
460         AutoBuffer<int> _d(m);
461         int* d = _d;
462 
463         for( i = i1; i < i2; i++ )
464         {
465             const uchar* sptr = src->ptr(m-1) + i;
466             float* dptr = dst->ptr<float>() + i;
467             int j, dist = m-1;
468 
469             for( j = m-1; j >= 0; j--, sptr -= sstep )
470             {
471                 dist = (dist + 1) & (sptr[0] == 0 ? 0 : -1);
472                 d[j] = dist;
473             }
474 
475             dist = m-1;
476             for( j = 0; j < m; j++, dptr += dstep )
477             {
478                 dist = dist + 1 - sat_tab[dist - d[j]];
479                 d[j] = dist;
480                 dptr[0] = sqr_tab[dist];
481             }
482         }
483     }
484 
485     const Mat* src;
486     Mat* dst;
487     const int* sat_tab;
488     const float* sqr_tab;
489 };
490 
491 struct DTRowInvoker : ParallelLoopBody
492 {
DTRowInvokercv::DTRowInvoker493     DTRowInvoker( Mat* _dst, const float* _sqr_tab, const float* _inv_tab )
494     {
495         dst = _dst;
496         sqr_tab = _sqr_tab;
497         inv_tab = _inv_tab;
498     }
499 
operator ()cv::DTRowInvoker500     void operator()( const Range& range ) const
501     {
502         const float inf = 1e15f;
503         int i, i1 = range.start, i2 = range.end;
504         int n = dst->cols;
505         AutoBuffer<uchar> _buf((n+2)*2*sizeof(float) + (n+2)*sizeof(int));
506         float* f = (float*)(uchar*)_buf;
507         float* z = f + n;
508         int* v = alignPtr((int*)(z + n + 1), sizeof(int));
509 
510         for( i = i1; i < i2; i++ )
511         {
512             float* d = dst->ptr<float>(i);
513             int p, q, k;
514 
515             v[0] = 0;
516             z[0] = -inf;
517             z[1] = inf;
518             f[0] = d[0];
519 
520             for( q = 1, k = 0; q < n; q++ )
521             {
522                 float fq = d[q];
523                 f[q] = fq;
524 
525                 for(;;k--)
526                 {
527                     p = v[k];
528                     float s = (fq + sqr_tab[q] - d[p] - sqr_tab[p])*inv_tab[q - p];
529                     if( s > z[k] )
530                     {
531                         k++;
532                         v[k] = q;
533                         z[k] = s;
534                         z[k+1] = inf;
535                         break;
536                     }
537                 }
538             }
539 
540             for( q = 0, k = 0; q < n; q++ )
541             {
542                 while( z[k+1] < q )
543                     k++;
544                 p = v[k];
545                 d[q] = std::sqrt(sqr_tab[std::abs(q - p)] + f[p]);
546             }
547         }
548     }
549 
550     Mat* dst;
551     const float* sqr_tab;
552     const float* inv_tab;
553 };
554 
555 static void
trueDistTrans(const Mat & src,Mat & dst)556 trueDistTrans( const Mat& src, Mat& dst )
557 {
558     const float inf = 1e15f;
559 
560     CV_Assert( src.size() == dst.size() );
561 
562     CV_Assert( src.type() == CV_8UC1 && dst.type() == CV_32FC1 );
563     int i, m = src.rows, n = src.cols;
564 
565     cv::AutoBuffer<uchar> _buf(std::max(m*2*sizeof(float) + (m*3+1)*sizeof(int), n*2*sizeof(float)));
566     // stage 1: compute 1d distance transform of each column
567     float* sqr_tab = (float*)(uchar*)_buf;
568     int* sat_tab = cv::alignPtr((int*)(sqr_tab + m*2), sizeof(int));
569     int shift = m*2;
570 
571     for( i = 0; i < m; i++ )
572         sqr_tab[i] = (float)(i*i);
573     for( i = m; i < m*2; i++ )
574         sqr_tab[i] = inf;
575     for( i = 0; i < shift; i++ )
576         sat_tab[i] = 0;
577     for( ; i <= m*3; i++ )
578         sat_tab[i] = i - shift;
579 
580     cv::parallel_for_(cv::Range(0, n), cv::DTColumnInvoker(&src, &dst, sat_tab, sqr_tab), src.total()/(double)(1<<16));
581 
582     // stage 2: compute modified distance transform for each row
583     float* inv_tab = sqr_tab + n;
584 
585     inv_tab[0] = sqr_tab[0] = 0.f;
586     for( i = 1; i < n; i++ )
587     {
588         inv_tab[i] = (float)(0.5/i);
589         sqr_tab[i] = (float)(i*i);
590     }
591 
592     cv::parallel_for_(cv::Range(0, m), cv::DTRowInvoker(&dst, sqr_tab, inv_tab));
593 }
594 
595 
596 /****************************************************************************************\
597  Non-inplace and Inplace 8u->8u Distance Transform for CityBlock (a.k.a. L1) metric
598  (C) 2006 by Jay Stavinzky.
599 \****************************************************************************************/
600 
601 //BEGIN ATS ADDITION
602 // 8-bit grayscale distance transform function
603 static void
distanceATS_L1_8u(const Mat & src,Mat & dst)604 distanceATS_L1_8u( const Mat& src, Mat& dst )
605 {
606     int width = src.cols, height = src.rows;
607 
608     int a;
609     uchar lut[256];
610     int x, y;
611 
612     const uchar *sbase = src.ptr();
613     uchar *dbase = dst.ptr();
614     int srcstep = (int)src.step;
615     int dststep = (int)dst.step;
616 
617     CV_Assert( src.type() == CV_8UC1 && dst.type() == CV_8UC1 );
618     CV_Assert( src.size() == dst.size() );
619 
620     ////////////////////// forward scan ////////////////////////
621     for( x = 0; x < 256; x++ )
622         lut[x] = cv::saturate_cast<uchar>(x+1);
623 
624     //init first pixel to max (we're going to be skipping it)
625     dbase[0] = (uchar)(sbase[0] == 0 ? 0 : 255);
626 
627     //first row (scan west only, skip first pixel)
628     for( x = 1; x < width; x++ )
629         dbase[x] = (uchar)(sbase[x] == 0 ? 0 : lut[dbase[x-1]]);
630 
631     for( y = 1; y < height; y++ )
632     {
633         sbase += srcstep;
634         dbase += dststep;
635 
636         //for left edge, scan north only
637         a = sbase[0] == 0 ? 0 : lut[dbase[-dststep]];
638         dbase[0] = (uchar)a;
639 
640         for( x = 1; x < width; x++ )
641         {
642             a = sbase[x] == 0 ? 0 : lut[MIN(a, dbase[x - dststep])];
643             dbase[x] = (uchar)a;
644         }
645     }
646 
647     ////////////////////// backward scan ///////////////////////
648 
649     a = dbase[width-1];
650 
651     // do last row east pixel scan here (skip bottom right pixel)
652     for( x = width - 2; x >= 0; x-- )
653     {
654         a = lut[a];
655         dbase[x] = (uchar)(CV_CALC_MIN_8U(a, dbase[x]));
656     }
657 
658     // right edge is the only error case
659     for( y = height - 2; y >= 0; y-- )
660     {
661         dbase -= dststep;
662 
663         // do right edge
664         a = lut[dbase[width-1+dststep]];
665         dbase[width-1] = (uchar)(MIN(a, dbase[width-1]));
666 
667         for( x = width - 2; x >= 0; x-- )
668         {
669             int b = dbase[x+dststep];
670             a = lut[MIN(a, b)];
671             a = MIN(a, dbase[x]);
672             dbase[x] = (uchar)(a);
673         }
674     }
675 }
676 //END ATS ADDITION
677 
678 }
679 
680 namespace cv
681 {
distanceTransform_L1_8U(InputArray _src,OutputArray _dst)682 static void distanceTransform_L1_8U(InputArray _src, OutputArray _dst)
683 {
684     Mat src = _src.getMat();
685 
686     CV_Assert( src.type() == CV_8UC1);
687 
688     _dst.create( src.size(), CV_8UC1);
689     Mat dst = _dst.getMat();
690 
691 #ifdef HAVE_IPP
692     CV_IPP_CHECK()
693     {
694         IppiSize roi = { src.cols, src.rows };
695         Ipp32s pMetrics[2] = { 1, 2 }; //L1, 3x3 mask
696         if (ippiDistanceTransform_3x3_8u_C1R(src.ptr<uchar>(), (int)src.step, dst.ptr<uchar>(), (int)dst.step, roi, pMetrics)>=0)
697         {
698             CV_IMPL_ADD(CV_IMPL_IPP);
699             return;
700         }
701         setIppErrorStatus();
702     }
703 #endif
704 
705     distanceATS_L1_8u(src, dst);
706 }
707 }
708 
709 // Wrapper function for distance transform group
distanceTransform(InputArray _src,OutputArray _dst,OutputArray _labels,int distType,int maskSize,int labelType)710 void cv::distanceTransform( InputArray _src, OutputArray _dst, OutputArray _labels,
711                             int distType, int maskSize, int labelType )
712 {
713     Mat src = _src.getMat(), labels;
714     bool need_labels = _labels.needed();
715 
716     CV_Assert( src.type() == CV_8UC1);
717 
718     _dst.create( src.size(), CV_32F);
719     Mat dst = _dst.getMat();
720 
721     if( need_labels )
722     {
723         CV_Assert( labelType == DIST_LABEL_PIXEL || labelType == DIST_LABEL_CCOMP );
724 
725         _labels.create(src.size(), CV_32S);
726         labels = _labels.getMat();
727         maskSize = CV_DIST_MASK_5;
728     }
729 
730     float _mask[5] = {0};
731 
732     if( maskSize != CV_DIST_MASK_3 && maskSize != CV_DIST_MASK_5 && maskSize != CV_DIST_MASK_PRECISE )
733         CV_Error( CV_StsBadSize, "Mask size should be 3 or 5 or 0 (presize)" );
734 
735     if( distType == CV_DIST_C || distType == CV_DIST_L1 )
736         maskSize = !need_labels ? CV_DIST_MASK_3 : CV_DIST_MASK_5;
737     else if( distType == CV_DIST_L2 && need_labels )
738         maskSize = CV_DIST_MASK_5;
739 
740     if( maskSize == CV_DIST_MASK_PRECISE )
741     {
742 
743 #ifdef HAVE_IPP
744         CV_IPP_CHECK()
745         {
746             if ((currentParallelFramework()==NULL) || (src.total()<(int)(1<<14)))
747             {
748                 IppStatus status;
749                 IppiSize roi = { src.cols, src.rows };
750                 Ipp8u *pBuffer;
751                 int bufSize=0;
752 
753                 status = ippiTrueDistanceTransformGetBufferSize_8u32f_C1R(roi, &bufSize);
754                 if (status>=0)
755                 {
756                     pBuffer = (Ipp8u *)ippMalloc( bufSize );
757                     status = ippiTrueDistanceTransform_8u32f_C1R(src.ptr<uchar>(),(int)src.step, dst.ptr<float>(), (int)dst.step, roi, pBuffer);
758                     ippFree( pBuffer );
759                     if (status>=0)
760                     {
761                         CV_IMPL_ADD(CV_IMPL_IPP);
762                         return;
763                     }
764                     setIppErrorStatus();
765                 }
766             }
767         }
768 #endif
769 
770         trueDistTrans( src, dst );
771         return;
772     }
773 
774     CV_Assert( distType == CV_DIST_C || distType == CV_DIST_L1 || distType == CV_DIST_L2 );
775 
776     getDistanceTransformMask( (distType == CV_DIST_C ? 0 :
777         distType == CV_DIST_L1 ? 1 : 2) + maskSize*10, _mask );
778 
779     Size size = src.size();
780 
781     int border = maskSize == CV_DIST_MASK_3 ? 1 : 2;
782     Mat temp( size.height + border*2, size.width + border*2, CV_32SC1 );
783 
784     if( !need_labels )
785     {
786         if( maskSize == CV_DIST_MASK_3 )
787         {
788 #if defined (HAVE_IPP) && (IPP_VERSION_MAJOR >= 7)
789             CV_IPP_CHECK()
790             {
791                 IppiSize roi = { src.cols, src.rows };
792                 if (ippiDistanceTransform_3x3_8u32f_C1R(src.ptr<uchar>(), (int)src.step, dst.ptr<float>(), (int)dst.step, roi, _mask)>=0)
793                 {
794                     CV_IMPL_ADD(CV_IMPL_IPP);
795                     return;
796                 }
797                 setIppErrorStatus();
798             }
799 #endif
800 
801             distanceTransform_3x3(src, temp, dst, _mask);
802         }
803         else
804         {
805 #if defined (HAVE_IPP) && (IPP_VERSION_MAJOR >= 7)
806             CV_IPP_CHECK()
807             {
808                 IppiSize roi = { src.cols, src.rows };
809                 if (ippiDistanceTransform_5x5_8u32f_C1R(src.ptr<uchar>(), (int)src.step, dst.ptr<float>(), (int)dst.step, roi, _mask)>=0)
810                 {
811                     CV_IMPL_ADD(CV_IMPL_IPP);
812                     return;
813                 }
814                 setIppErrorStatus();
815             }
816 #endif
817 
818             distanceTransform_5x5(src, temp, dst, _mask);
819         }
820     }
821     else
822     {
823         labels.setTo(Scalar::all(0));
824 
825         if( labelType == CV_DIST_LABEL_CCOMP )
826         {
827             Mat zpix = src == 0;
828             connectedComponents(zpix, labels, 8, CV_32S);
829         }
830         else
831         {
832             int k = 1;
833             for( int i = 0; i < src.rows; i++ )
834             {
835                 const uchar* srcptr = src.ptr(i);
836                 int* labelptr = labels.ptr<int>(i);
837 
838                 for( int j = 0; j < src.cols; j++ )
839                     if( srcptr[j] == 0 )
840                         labelptr[j] = k++;
841             }
842         }
843 
844        distanceTransformEx_5x5( src, temp, dst, labels, _mask );
845     }
846 }
847 
distanceTransform(InputArray _src,OutputArray _dst,int distanceType,int maskSize,int dstType)848 void cv::distanceTransform( InputArray _src, OutputArray _dst,
849                             int distanceType, int maskSize, int dstType)
850 {
851     if (distanceType == CV_DIST_L1 && dstType==CV_8U)
852         distanceTransform_L1_8U(_src, _dst);
853     else
854         distanceTransform(_src, _dst, noArray(), distanceType, maskSize, DIST_LABEL_PIXEL);
855 
856 }
857 
858 CV_IMPL void
cvDistTransform(const void * srcarr,void * dstarr,int distType,int maskSize,const float *,void * labelsarr,int labelType)859 cvDistTransform( const void* srcarr, void* dstarr,
860                 int distType, int maskSize,
861                 const float * /*mask*/,
862                 void* labelsarr, int labelType )
863 {
864     cv::Mat src = cv::cvarrToMat(srcarr);
865     const cv::Mat dst = cv::cvarrToMat(dstarr);
866     const cv::Mat labels = cv::cvarrToMat(labelsarr);
867 
868     cv::distanceTransform(src, dst, labelsarr ? cv::_OutputArray(labels) : cv::_OutputArray(),
869                           distType, maskSize, labelType);
870 
871 }
872 
873 
874 /* End of file. */
875