--- /dev/null
+/*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*/
+
+#include "_cv.h"
+
+/****************************************************************************************\
+* Watershed *
+\****************************************************************************************/
+
+typedef struct CvWSNode
+{
+ struct CvWSNode* next;
+ int mask_ofs;
+ int img_ofs;
+}
+CvWSNode;
+
+typedef struct CvWSQueue
+{
+ CvWSNode* first;
+ CvWSNode* last;
+}
+CvWSQueue;
+
+static CvWSNode*
+icvAllocWSNodes( CvMemStorage* storage )
+{
+ CvWSNode* n = 0;
+
+ CV_FUNCNAME( "icvAllocWSNodes" );
+
+ __BEGIN__;
+
+ int i, count = (storage->block_size - sizeof(CvMemBlock))/sizeof(*n) - 1;
+
+ CV_CALL( n = (CvWSNode*)cvMemStorageAlloc( storage, count*sizeof(*n) ));
+ for( i = 0; i < count-1; i++ )
+ n[i].next = n + i + 1;
+ n[count-1].next = 0;
+
+ __END__;
+
+ return n;
+}
+
+
+CV_IMPL void
+cvWatershed( const CvArr* srcarr, CvArr* dstarr )
+{
+ const int IN_QUEUE = -2;
+ const int WSHED = -1;
+ const int NQ = 256;
+ CvMemStorage* storage = 0;
+
+ CV_FUNCNAME( "cvWatershed" );
+
+ __BEGIN__;
+
+ CvMat sstub, *src;
+ CvMat dstub, *dst;
+ CvSize size;
+ CvWSNode* free_node = 0, *node;
+ CvWSQueue q[NQ];
+ int active_queue;
+ int i, j;
+ int db, dg, dr;
+ int* mask;
+ uchar* img;
+ int mstep, istep;
+ int subs_tab[513];
+
+ // MAX(a,b) = b + MAX(a-b,0)
+ #define ws_max(a,b) ((b) + subs_tab[(a)-(b)+NQ])
+ // MIN(a,b) = a - MAX(a-b,0)
+ #define ws_min(a,b) ((a) - subs_tab[(a)-(b)+NQ])
+
+ #define ws_push(idx,mofs,iofs) \
+ { \
+ if( !free_node ) \
+ CV_CALL( free_node = icvAllocWSNodes( storage ));\
+ node = free_node; \
+ free_node = free_node->next;\
+ node->next = 0; \
+ node->mask_ofs = mofs; \
+ node->img_ofs = iofs; \
+ if( q[idx].last ) \
+ q[idx].last->next=node; \
+ else \
+ q[idx].first = node; \
+ q[idx].last = node; \
+ }
+
+ #define ws_pop(idx,mofs,iofs) \
+ { \
+ node = q[idx].first; \
+ q[idx].first = node->next; \
+ if( !node->next ) \
+ q[idx].last = 0; \
+ node->next = free_node; \
+ free_node = node; \
+ mofs = node->mask_ofs; \
+ iofs = node->img_ofs; \
+ }
+
+ #define c_diff(ptr1,ptr2,diff) \
+ { \
+ db = abs((ptr1)[0] - (ptr2)[0]);\
+ dg = abs((ptr1)[1] - (ptr2)[1]);\
+ dr = abs((ptr1)[2] - (ptr2)[2]);\
+ diff = ws_max(db,dg); \
+ diff = ws_max(diff,dr); \
+ assert( 0 <= diff && diff <= 255 ); \
+ }
+
+ CV_CALL( src = cvGetMat( srcarr, &sstub ));
+ CV_CALL( dst = cvGetMat( dstarr, &dstub ));
+
+ if( CV_MAT_TYPE(src->type) != CV_8UC3 )
+ CV_ERROR( CV_StsUnsupportedFormat, "Only 8-bit, 3-channel input images are supported" );
+
+ if( CV_MAT_TYPE(dst->type) != CV_32SC1 )
+ CV_ERROR( CV_StsUnsupportedFormat,
+ "Only 32-bit, 1-channel output images are supported" );
+
+ if( !CV_ARE_SIZES_EQ( src, dst ))
+ CV_ERROR( CV_StsUnmatchedSizes, "The input and output images must have the same size" );
+
+ size = cvGetMatSize(src);
+
+ CV_CALL( storage = cvCreateMemStorage() );
+
+ istep = src->step;
+ img = src->data.ptr;
+ mstep = dst->step / sizeof(mask[0]);
+ mask = dst->data.i;
+
+ memset( q, 0, NQ*sizeof(q[0]) );
+
+ for( i = 0; i < 256; i++ )
+ subs_tab[i] = 0;
+ for( i = 256; i <= 512; i++ )
+ subs_tab[i] = i - 256;
+
+ // draw a pixel-wide border of dummy "watershed" (i.e. boundary) pixels
+ for( j = 0; j < size.width; j++ )
+ mask[j] = mask[j + mstep*(size.height-1)] = WSHED;
+
+ // initial phase: put all the neighbor pixels of each marker to the ordered queue -
+ // determine the initial boundaries of the basins
+ for( i = 1; i < size.height-1; i++ )
+ {
+ img += istep; mask += mstep;
+ mask[0] = mask[size.width-1] = WSHED;
+
+ for( j = 1; j < size.width-1; j++ )
+ {
+ int* m = mask + j;
+ if( m[0] < 0 ) m[0] = 0;
+ if( m[0] == 0 && (m[-1] > 0 || m[1] > 0 || m[-mstep] > 0 || m[mstep] > 0) )
+ {
+ uchar* ptr = img + j*3;
+ int idx = 256, t;
+ if( m[-1] > 0 )
+ c_diff( ptr, ptr - 3, idx );
+ if( m[1] > 0 )
+ {
+ c_diff( ptr, ptr + 3, t );
+ idx = ws_min( idx, t );
+ }
+ if( m[-mstep] > 0 )
+ {
+ c_diff( ptr, ptr - istep, t );
+ idx = ws_min( idx, t );
+ }
+ if( m[mstep] > 0 )
+ {
+ c_diff( ptr, ptr + istep, t );
+ idx = ws_min( idx, t );
+ }
+ assert( 0 <= idx && idx <= 255 );
+ ws_push( idx, i*mstep + j, i*istep + j*3 );
+ m[0] = IN_QUEUE;
+ }
+ }
+ }
+
+ // find the first non-empty queue
+ for( i = 0; i < NQ; i++ )
+ if( q[i].first )
+ break;
+
+ // if there is no markers, exit immediately
+ if( i == NQ )
+ EXIT;
+
+ active_queue = i;
+ img = src->data.ptr;
+ mask = dst->data.i;
+
+ // recursively fill the basins
+ for(;;)
+ {
+ int mofs, iofs;
+ int lab = 0, t;
+ int* m;
+ uchar* ptr;
+
+ if( q[active_queue].first == 0 )
+ {
+ for( i = active_queue+1; i < NQ; i++ )
+ if( q[i].first )
+ break;
+ if( i == NQ )
+ break;
+ active_queue = i;
+ }
+
+ ws_pop( active_queue, mofs, iofs );
+
+ m = mask + mofs;
+ ptr = img + iofs;
+ t = m[-1];
+ if( t > 0 ) lab = t;
+ t = m[1];
+ if( t > 0 )
+ {
+ if( lab == 0 ) lab = t;
+ else if( t != lab ) lab = WSHED;
+ }
+ t = m[-mstep];
+ if( t > 0 )
+ {
+ if( lab == 0 ) lab = t;
+ else if( t != lab ) lab = WSHED;
+ }
+ t = m[mstep];
+ if( t > 0 )
+ {
+ if( lab == 0 ) lab = t;
+ else if( t != lab ) lab = WSHED;
+ }
+ assert( lab != 0 );
+ m[0] = lab;
+ if( lab == WSHED )
+ continue;
+
+ if( m[-1] == 0 )
+ {
+ c_diff( ptr, ptr - 3, t );
+ ws_push( t, mofs - 1, iofs - 3 );
+ active_queue = ws_min( active_queue, t );
+ m[-1] = IN_QUEUE;
+ }
+ if( m[1] == 0 )
+ {
+ c_diff( ptr, ptr + 3, t );
+ ws_push( t, mofs + 1, iofs + 3 );
+ active_queue = ws_min( active_queue, t );
+ m[1] = IN_QUEUE;
+ }
+ if( m[-mstep] == 0 )
+ {
+ c_diff( ptr, ptr - istep, t );
+ ws_push( t, mofs - mstep, iofs - istep );
+ active_queue = ws_min( active_queue, t );
+ m[-mstep] = IN_QUEUE;
+ }
+ if( m[mstep] == 0 )
+ {
+ c_diff( ptr, ptr + 3, t );
+ ws_push( t, mofs + mstep, iofs + istep );
+ active_queue = ws_min( active_queue, t );
+ m[mstep] = IN_QUEUE;
+ }
+ }
+
+ __END__;
+
+ cvReleaseMemStorage( &storage );
+}
+
+
+void cv::watershed( const Mat& src, Mat& markers )
+{
+ CvMat _src = src, _markers = markers;
+ cvWatershed( &_src, &_markers );
+}
+
+
+/****************************************************************************************\
+* Meanshift *
+\****************************************************************************************/
+
+CV_IMPL void
+cvPyrMeanShiftFiltering( const CvArr* srcarr, CvArr* dstarr,
+ double sp0, double sr, int max_level,
+ CvTermCriteria termcrit )
+{
+ const int cn = 3;
+ const int MAX_LEVELS = 8;
+ CvMat* src_pyramid[MAX_LEVELS+1];
+ CvMat* dst_pyramid[MAX_LEVELS+1];
+ CvMat* mask0 = 0;
+ int i, j, level;
+ //uchar* submask = 0;
+
+ #define cdiff(ofs0) (tab[c0-dptr[ofs0]+255] + \
+ tab[c1-dptr[(ofs0)+1]+255] + tab[c2-dptr[(ofs0)+2]+255] >= isr22)
+
+ memset( src_pyramid, 0, sizeof(src_pyramid) );
+ memset( dst_pyramid, 0, sizeof(dst_pyramid) );
+
+ CV_FUNCNAME( "cvPyrMeanShiftFiltering" );
+
+ __BEGIN__;
+
+ double sr2 = sr * sr;
+ int isr2 = cvRound(sr2), isr22 = MAX(isr2,16);
+ int tab[768];
+ CvMat sstub0, *src0;
+ CvMat dstub0, *dst0;
+
+ CV_CALL( src0 = cvGetMat( srcarr, &sstub0 ));
+ CV_CALL( dst0 = cvGetMat( dstarr, &dstub0 ));
+
+ if( CV_MAT_TYPE(src0->type) != CV_8UC3 )
+ CV_ERROR( CV_StsUnsupportedFormat, "Only 8-bit, 3-channel images are supported" );
+
+ if( !CV_ARE_TYPES_EQ( src0, dst0 ))
+ CV_ERROR( CV_StsUnmatchedFormats, "The input and output images must have the same type" );
+
+ if( !CV_ARE_SIZES_EQ( src0, dst0 ))
+ CV_ERROR( CV_StsUnmatchedSizes, "The input and output images must have the same size" );
+
+ if( (unsigned)max_level > (unsigned)MAX_LEVELS )
+ CV_ERROR( CV_StsOutOfRange, "The number of pyramid levels is too large or negative" );
+
+ if( !(termcrit.type & CV_TERMCRIT_ITER) )
+ termcrit.max_iter = 5;
+ termcrit.max_iter = MAX(termcrit.max_iter,1);
+ termcrit.max_iter = MIN(termcrit.max_iter,100);
+ if( !(termcrit.type & CV_TERMCRIT_EPS) )
+ termcrit.epsilon = 1.f;
+ termcrit.epsilon = MAX(termcrit.epsilon, 0.f);
+
+ for( i = 0; i < 768; i++ )
+ tab[i] = (i - 255)*(i - 255);
+
+ // 1. construct pyramid
+ src_pyramid[0] = src0;
+ dst_pyramid[0] = dst0;
+ for( level = 1; level <= max_level; level++ )
+ {
+ CV_CALL( src_pyramid[level] = cvCreateMat( (src_pyramid[level-1]->rows+1)/2,
+ (src_pyramid[level-1]->cols+1)/2, src_pyramid[level-1]->type ));
+ CV_CALL( dst_pyramid[level] = cvCreateMat( src_pyramid[level]->rows,
+ src_pyramid[level]->cols, src_pyramid[level]->type ));
+ CV_CALL( cvPyrDown( src_pyramid[level-1], src_pyramid[level] ));
+ //CV_CALL( cvResize( src_pyramid[level-1], src_pyramid[level], CV_INTER_AREA ));
+ }
+
+ CV_CALL( mask0 = cvCreateMat( src0->rows, src0->cols, CV_8UC1 ));
+ //CV_CALL( submask = (uchar*)cvAlloc( (sp+2)*(sp+2) ));
+
+ // 2. apply meanshift, starting from the pyramid top (i.e. the smallest layer)
+ for( level = max_level; level >= 0; level-- )
+ {
+ CvMat* src = src_pyramid[level];
+ CvSize size = cvGetMatSize(src);
+ uchar* sptr = src->data.ptr;
+ int sstep = src->step;
+ uchar* mask = 0;
+ int mstep = 0;
+ uchar* dptr;
+ int dstep;
+ float sp = (float)(sp0 / (1 << level));
+ sp = MAX( sp, 1 );
+
+ if( level < max_level )
+ {
+ CvSize size1 = cvGetMatSize(dst_pyramid[level+1]);
+ CvMat m = cvMat( size.height, size.width, CV_8UC1, mask0->data.ptr );
+ dstep = dst_pyramid[level+1]->step;
+ dptr = dst_pyramid[level+1]->data.ptr + dstep + cn;
+ mstep = m.step;
+ mask = m.data.ptr + mstep;
+ //cvResize( dst_pyramid[level+1], dst_pyramid[level], CV_INTER_CUBIC );
+ cvPyrUp( dst_pyramid[level+1], dst_pyramid[level] );
+ cvZero( &m );
+
+ for( i = 1; i < size1.height-1; i++, dptr += dstep - (size1.width-2)*3, mask += mstep*2 )
+ {
+ for( j = 1; j < size1.width-1; j++, dptr += cn )
+ {
+ int c0 = dptr[0], c1 = dptr[1], c2 = dptr[2];
+ mask[j*2 - 1] = cdiff(-3) || cdiff(3) || cdiff(-dstep-3) || cdiff(-dstep) ||
+ cdiff(-dstep+3) || cdiff(dstep-3) || cdiff(dstep) || cdiff(dstep+3);
+ }
+ }
+
+ cvDilate( &m, &m, 0, 1 );
+ mask = m.data.ptr;
+ }
+
+ dptr = dst_pyramid[level]->data.ptr;
+ dstep = dst_pyramid[level]->step;
+
+ for( i = 0; i < size.height; i++, sptr += sstep - size.width*3,
+ dptr += dstep - size.width*3,
+ mask += mstep )
+ {
+ for( j = 0; j < size.width; j++, sptr += 3, dptr += 3 )
+ {
+ int x0 = j, y0 = i, x1, y1, iter;
+ int c0, c1, c2;
+
+ if( mask && !mask[j] )
+ continue;
+
+ c0 = sptr[0], c1 = sptr[1], c2 = sptr[2];
+
+ // iterate meanshift procedure
+ for( iter = 0; iter < termcrit.max_iter; iter++ )
+ {
+ uchar* ptr;
+ int x, y, count = 0;
+ int minx, miny, maxx, maxy;
+ int s0 = 0, s1 = 0, s2 = 0, sx = 0, sy = 0;
+ double icount;
+ int stop_flag;
+
+ //mean shift: process pixels in window (p-sigmaSp)x(p+sigmaSp)
+ minx = cvRound(x0 - sp); minx = MAX(minx, 0);
+ miny = cvRound(y0 - sp); miny = MAX(miny, 0);
+ maxx = cvRound(x0 + sp); maxx = MIN(maxx, size.width-1);
+ maxy = cvRound(y0 + sp); maxy = MIN(maxy, size.height-1);
+ ptr = sptr + (miny - i)*sstep + (minx - j)*3;
+
+ for( y = miny; y <= maxy; y++, ptr += sstep - (maxx-minx+1)*3 )
+ {
+ int row_count = 0;
+ x = minx;
+ for( ; x + 3 <= maxx; x += 4, ptr += 12 )
+ {
+ int t0 = ptr[0], t1 = ptr[1], t2 = ptr[2];
+ if( tab[t0-c0+255] + tab[t1-c1+255] + tab[t2-c2+255] <= isr2 )
+ {
+ s0 += t0; s1 += t1; s2 += t2;
+ sx += x; row_count++;
+ }
+ t0 = ptr[3], t1 = ptr[4], t2 = ptr[5];
+ if( tab[t0-c0+255] + tab[t1-c1+255] + tab[t2-c2+255] <= isr2 )
+ {
+ s0 += t0; s1 += t1; s2 += t2;
+ sx += x+1; row_count++;
+ }
+ t0 = ptr[6], t1 = ptr[7], t2 = ptr[8];
+ if( tab[t0-c0+255] + tab[t1-c1+255] + tab[t2-c2+255] <= isr2 )
+ {
+ s0 += t0; s1 += t1; s2 += t2;
+ sx += x+2; row_count++;
+ }
+ t0 = ptr[9], t1 = ptr[10], t2 = ptr[11];
+ if( tab[t0-c0+255] + tab[t1-c1+255] + tab[t2-c2+255] <= isr2 )
+ {
+ s0 += t0; s1 += t1; s2 += t2;
+ sx += x+3; row_count++;
+ }
+ }
+
+ for( ; x <= maxx; x++, ptr += 3 )
+ {
+ int t0 = ptr[0], t1 = ptr[1], t2 = ptr[2];
+ if( tab[t0-c0+255] + tab[t1-c1+255] + tab[t2-c2+255] <= isr2 )
+ {
+ s0 += t0; s1 += t1; s2 += t2;
+ sx += x; row_count++;
+ }
+ }
+ count += row_count;
+ sy += y*row_count;
+ }
+
+ if( count == 0 )
+ break;
+
+ icount = 1./count;
+ x1 = cvRound(sx*icount);
+ y1 = cvRound(sy*icount);
+ s0 = cvRound(s0*icount);
+ s1 = cvRound(s1*icount);
+ s2 = cvRound(s2*icount);
+
+ stop_flag = (x0 == x1 && y0 == y1) || abs(x1-x0) + abs(y1-y0) +
+ tab[s0 - c0 + 255] + tab[s1 - c1 + 255] +
+ tab[s2 - c2 + 255] <= termcrit.epsilon;
+
+ x0 = x1; y0 = y1;
+ c0 = s0; c1 = s1; c2 = s2;
+
+ if( stop_flag )
+ break;
+ }
+
+ dptr[0] = (uchar)c0;
+ dptr[1] = (uchar)c1;
+ dptr[2] = (uchar)c2;
+ }
+ }
+ }
+
+ __END__;
+
+ for( i = 1; i <= MAX_LEVELS; i++ )
+ {
+ cvReleaseMat( &src_pyramid[i] );
+ cvReleaseMat( &dst_pyramid[i] );
+ }
+ cvReleaseMat( &mask0 );
+}
+
projects / opencv / blobdiff