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vigra/seededregiongrowing3d.hxx |

    00001 /************************************************************************/
    00002 /*                                                                      */
    00003 /*     Copyright 2003-2007 by Kasim Terzic, Christian-Dennis Rahn       */
    00004 /*                        and Ullrich Koethe                            */
    00005 /*                                                                      */
    00006 /*    This file is part of the VIGRA computer vision library.           */
    00007 /*    The VIGRA Website is                                              */
    00008 /*        http://hci.iwr.uni-heidelberg.de/vigra/                       */
    00009 /*    Please direct questions, bug reports, and contributions to        */
    00010 /*        ullrich.koethe@iwr.uni-heidelberg.de    or                    */
    00011 /*        vigra@informatik.uni-hamburg.de                               */
    00012 /*                                                                      */
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    00020 /*    conditions:                                                       */
    00021 /*                                                                      */
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    00024 /*    Software.                                                         */
    00025 /*                                                                      */
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    00034 /*                                                                      */
    00035 /************************************************************************/
    00036
    00037 #ifndef VIGRA_SEEDEDREGIONGROWING_3D_HXX
    00038 #define VIGRA_SEEDEDREGIONGROWING_3D_HXX
    00039
    00040 #include <vector>
    00041 #include <stack>
    00042 #include <queue>
    00043 #include "utilities.hxx"
    00044 #include "stdimage.hxx"
    00045 #include "stdimagefunctions.hxx"
    00046 #include "seededregiongrowing.hxx"
    00047 #include "multi_pointoperators.hxx"
    00048 #include "voxelneighborhood.hxx"
    00049
    00050 namespace vigra {
    00051
    00052 namespace detail {
    00053
    00054 template <class COST, class Diff_type>
    00055 class SeedRgVoxel
    00056 {
    00057 public:
    00058     Diff_type location_, nearest_;
    00059     COST cost_;
    00060     int count_;
    00061     int label_;
    00062     int dist_;
    00063
    00064     SeedRgVoxel()
    00065     //: location_(0,0,0), nearest_(0,0,0), cost_(0), count_(0), label_(0)
    00066     {
    00067         location_ = Diff_type(0,0,0);
    00068         nearest_ = Diff_type(0,0,0);
    00069         cost_ = 0;
    00070         count_ = 0;
    00071         label_ = 0;
    00072     }
    00073
    00074     SeedRgVoxel(Diff_type const & location, Diff_type const & nearest,
    00075                 COST const & cost, int const & count, int const & label)
    00076     : location_(location), nearest_(nearest),
    00077       cost_(cost), count_(count), label_(label)
    00078     {
    00079         int dx = location_[0] - nearest_[0];
    00080         int dy = location_[1] - nearest_[1];
    00081         int dz = location_[2] - nearest_[2];
    00082         dist_ = dx * dx + dy * dy + dz * dz;
    00083     }
    00084
    00085     void set(Diff_type const & location, Diff_type const & nearest,
    00086              COST const & cost, int const & count, int const & label)
    00087     {
    00088         location_ = location;
    00089         nearest_ = nearest;
    00090         cost_ = cost;
    00091         count_ = count;
    00092         label_ = label;
    00093
    00094         int dx = location_[0] - nearest_[0];
    00095         int dy = location_[1] - nearest_[1];
    00096         int dz = location_[2] - nearest_[2];
    00097         dist_ = dx * dx + dy * dy + dz * dz;
    00098     }
    00099
    00100     struct Compare
    00101     {
    00102         // must implement > since priority_queue looks for largest element
    00103         bool operator()(SeedRgVoxel const & l,
    00104                         SeedRgVoxel const & r) const
    00105         {
    00106             if(r.cost_ == l.cost_)
    00107             {
    00108                 if(r.dist_ == l.dist_) return r.count_ < l.count_;
    00109
    00110                 return r.dist_ < l.dist_;
    00111             }
    00112
    00113             return r.cost_ < l.cost_;
    00114         }
    00115         bool operator()(SeedRgVoxel const * l,
    00116                         SeedRgVoxel const * r) const
    00117         {
    00118             if(r->cost_ == l->cost_)
    00119             {
    00120                 if(r->dist_ == l->dist_) return r->count_ < l->count_;
    00121
    00122                 return r->dist_ < l->dist_;
    00123             }
    00124
    00125             return r->cost_ < l->cost_;
    00126         }
    00127     };
    00128
    00129     struct Allocator
    00130     {
    00131         ~Allocator()
    00132         {
    00133             while(!freelist_.empty())
    00134             {
    00135                 delete freelist_.top();
    00136                 freelist_.pop();
    00137             }
    00138         }
    00139
    00140         SeedRgVoxel * create(Diff_type const & location, Diff_type const & nearest,
    00141                              COST const & cost, int const & count, int const & label)
    00142         {
    00143             if(!freelist_.empty())
    00144             {
    00145                 SeedRgVoxel * res = freelist_.top();
    00146                 freelist_.pop();
    00147                 res->set(location, nearest, cost, count, label);
    00148                 return res;
    00149             }
    00150
    00151             return new SeedRgVoxel(location, nearest, cost, count, label);
    00152         }
    00153
    00154         void dismiss(SeedRgVoxel * p)
    00155         {
    00156             freelist_.push(p);
    00157         }
    00158
    00159         std::stack<SeedRgVoxel<COST,Diff_type> *> freelist_;
    00160     };
    00161 };
    00162
    00163 } // namespace detail
    00164
    00165 /** \addtogroup SeededRegionGrowing
    00166 */
    00167 //@{
    00168
    00169 /********************************************************/
    00170 /*                                                      */
    00171 /*                    seededRegionGrowing3D             */
    00172 /*                                                      */
    00173 /********************************************************/
    00174
    00175 /** \brief Three-dimensional Region Segmentation by means of Seeded Region Growing.
    00176
    00177     This algorithm implements seeded region growing as described in
    00178
    00179     The seed image is a partly segmented multi-dimensional array which contains uniquely
    00180     labeled regions (the seeds) and unlabeled voxels (the candidates, label 0).
    00181     Seed regions can be as large as you wish and as small as one voxel. If
    00182     there are no candidates, the algorithm will simply copy the seed array
    00183     into the output array. Otherwise it will aggregate the candidates into
    00184     the existing regions so that a cost function is minimized.
    00185     Candidates are taken from the neighborhood of the already assigned pixels,
    00186     where the type of neighborhood is determined by parameter <tt>neighborhood</tt>
    00187     which can take the values <tt>NeighborCode3DSix()</tt> (the default)
    00188     or <tt>NeighborCode3DTwentySix()</tt>. The algorithm basically works as follows
    00189     (illustrated for 6-neighborhood, but 26-neighborhood works in the same way):
    00190
    00191     <ol>
    00192
    00193     <li> Find all candidate pixels that are 6-adjacent to a seed region.
    00194     Calculate the cost for aggregating each candidate into its adjacent region
    00195     and put the candidates into a priority queue.
    00196
    00197     <li> While( priority queue is not empty)
    00198
    00199         <ol>
    00200
    00201         <li> Take the candidate with least cost from the queue. If it has not
    00202         already been merged, merge it with it's adjacent region.
    00203
    00204         <li> Put all candidates that are 4-adjacent to the pixel just processed
    00205         into the priority queue.
    00206
    00207         </ol>
    00208
    00209     </ol>
    00210
    00211     <tt>SRGType</tt> can take the following values:
    00212
    00213     <DL>
    00214     <DT><tt>CompleteGrow</tt> <DD> produce a complete tesselation of the volume (default).
    00215     <DT><tt>KeepContours</tt> <DD> keep a 1-voxel wide unlabeled contour between all regions.
    00216     <DT><tt>StopAtThreshold</tt> <DD> stop when the boundary indicator values exceed the
    00217                              threshold given by parameter <tt>max_cost</tt>.
    00218     <DT><tt>KeepContours | StopAtThreshold</tt> <DD> keep 1-voxel wide contour and stop at given <tt>max_cost</tt>.
    00219     </DL>
    00220
    00221     The cost is determined jointly by the source array and the
    00222     region statistics functor. The source array contains feature values for each
    00223     pixel which will be used by the region statistics functor to calculate and
    00224     update statistics for each region and to calculate the cost for each
    00225     candidate. The <TT>RegionStatisticsArray</TT> must be compatible to the
    00226     \ref ArrayOfRegionStatistics functor and contains an <em> array</em> of
    00227     statistics objects for each region. The indices must correspond to the
    00228     labels of the seed regions. The statistics for the initial regions must have
    00229     been calculated prior to calling <TT>seededRegionGrowing3D()</TT>
    00230
    00231     For each candidate
    00232     <TT>x</TT> that is adjacent to region <TT>i</TT>, the algorithm will call
    00233     <TT>stats[i].cost(as(x))</TT> to get the cost (where <TT>x</TT> is a <TT>SrcImageIterator</TT>
    00234     and <TT>as</TT> is
    00235     the SrcAccessor). When a candidate has been merged with a region, the
    00236     statistics are updated by calling <TT>stats[i].operator()(as(x))</TT>. Since
    00237     the <TT>RegionStatisticsArray</TT> is passed by reference, this will overwrite
    00238     the original statistics.
    00239
    00240     If a candidate could be merged into more than one regions with identical
    00241     cost, the algorithm will favour the nearest region. If <tt>StopAtThreshold</tt> is active,
    00242     and the cost of the current candidate at any point in the algorithm exceeds the optional
    00243     <tt>max_cost</tt> value (which defaults to <tt>NumericTraits<double>::max()</tt>),
    00244     region growing is aborted, and all voxels not yet assigned to a region remain unlabeled.
    00245
    00246     In some cases, the cost only depends on the feature value of the current
    00247     voxel. Then the update operation will simply be a no-op, and the <TT>cost()</TT>
    00248     function returns its argument. This behavior is implemented by the
    00249     \ref SeedRgDirectValueFunctor.
    00250
    00251     <b> Declarations:</b>
    00252
    00253     pass arguments explicitly:
    00254     \code
    00255     namespace vigra {
    00256         template <class SrcImageIterator, class Shape, class SrcAccessor,
    00257                   class SeedImageIterator, class SeedAccessor,
    00258                   class DestImageIterator, class DestAccessor,
    00259                   class RegionStatisticsArray, class Neighborhood>
    00260         void
    00261         seededRegionGrowing3D(SrcImageIterator srcul, Shape shape, SrcAccessor as,
    00262                               SeedImageIterator seedsul, SeedAccessor aseeds,
    00263                               DestImageIterator destul, DestAccessor ad,
    00264                               RegionStatisticsArray & stats,
    00265                               SRGType srgType = CompleteGrow,
    00266                               Neighborhood neighborhood = NeighborCode3DSix(),
    00267                               double max_cost = NumericTraits<double>::max());
    00268     }
    00269     \endcode
    00270
    00271     use argument objects in conjunction with \ref ArgumentObjectFactories :
    00272     \code
    00273     namespace vigra {
    00274         template <class SrcImageIterator, class Shape, class SrcAccessor,
    00275                   class SeedImageIterator, class SeedAccessor,
    00276                   class DestImageIterator, class DestAccessor,
    00277                   class RegionStatisticsArray, class Neighborhood>
    00278         void
    00279         seededRegionGrowing3D(triple<SrcImageIterator, Shape, SrcAccessor> src,
    00280                               pair<SeedImageIterator, SeedAccessor> seeds,
    00281                               pair<DestImageIterator, DestAccessor> dest,
    00282                               RegionStatisticsArray & stats,
    00283                               SRGType srgType = CompleteGrow,
    00284                               Neighborhood neighborhood = NeighborCode3DSix(),
    00285                               double max_cost = NumericTraits<double>::max());
    00286     }
    00287     \endcode
    00288
    00289 */
    00290 doxygen_overloaded_function(template <...> void seededRegionGrowing3D)
    00291
    00292 template <class SrcImageIterator, class Diff_type, class SrcAccessor,
    00293           class SeedImageIterator, class SeedAccessor,
    00294           class DestImageIterator, class DestAccessor,
    00295           class RegionStatisticsArray, class Neighborhood>
    00296 void
    00297 seededRegionGrowing3D(SrcImageIterator srcul, Diff_type shape, SrcAccessor as,
    00298                       SeedImageIterator seedsul, SeedAccessor aseeds,
    00299                       DestImageIterator destul, DestAccessor ad,
    00300                       RegionStatisticsArray & stats,
    00301                       SRGType srgType,
    00302                       Neighborhood,
    00303                       double max_cost)
    00304 {
    00305     //SrcImageIterator srclr = srcul + shape;
    00306     //int w = srclr.x - srcul.x;
    00307     int w = shape[0];
    00308     //int h = srclr.y - srcul.y;
    00309     int h = shape[1];
    00310     //int d = srclr.z - srcul.z;
    00311     int d = shape[2];
    00312     int count = 0;
    00313
    00314     SrcImageIterator isy = srcul, isx = srcul, isz = srcul;  // iterators for the src image
    00315
    00316     typedef typename RegionStatisticsArray::value_type RegionStatistics;
    00317     typedef typename PromoteTraits<typename RegionStatistics::cost_type, double>::Promote CostType;
    00318     typedef detail::SeedRgVoxel<CostType, Diff_type> Voxel;
    00319
    00320     typename Voxel::Allocator allocator;
    00321
    00322     typedef std::priority_queue< Voxel *,
    00323                                  std::vector<Voxel *>,
    00324                                  typename Voxel::Compare >  SeedRgVoxelHeap;
    00325     typedef MultiArray<3, int> IVolume;
    00326
    00327     // copy seed image in an image with border
    00328     Diff_type regionshape = shape + Diff_type(2,2,2);
    00329     IVolume regions(regionshape);
    00330     MultiIterator<3,int> ir = regions.traverser_begin();
    00331     ir = ir + Diff_type(1,1,1);
    00332
    00333     //IVolume::Iterator iry, irx, irz;
    00334     MultiIterator<3,int> iry, irx, irz;
    00335
    00336     //initImageBorder(destImageRange(regions), 1, SRGWatershedLabel);
    00337     initMultiArrayBorder(destMultiArrayRange(regions), 1, SRGWatershedLabel);
    00338
    00339     copyMultiArray(seedsul, Diff_type(w,h,d), aseeds, ir, AccessorTraits<int>::default_accessor());
    00340
    00341     // allocate and init memory for the results
    00342
    00343     SeedRgVoxelHeap pheap;
    00344     int cneighbor;
    00345
    00346     #if 0
    00347     static const Diff_type dist[] = { Diff_type(-1, 0, 0), Diff_type( 0,-1, 0),
    00348                                       Diff_type( 1, 0, 0), Diff_type( 0, 1, 0),
    00349                                       Diff_type( 0, 0,-1), Diff_type( 0, 0, 1) };
    00350     #endif
    00351
    00352     typedef typename Neighborhood::Direction Direction;
    00353     int directionCount = Neighborhood::DirectionCount;
    00354
    00355     Diff_type pos(0,0,0);
    00356
    00357     for(isz=srcul, irz=ir, pos[2]=0; pos[2]<d;
    00358             pos[2]++, isz.dim2()++, irz.dim2()++)
    00359     {
    00360         //std::cerr << "Z = " << pos[2] << std::endl;
    00361
    00362         for(isy=isz, iry=irz, pos[1]=0; pos[1]<h;
    00363             pos[1]++, isy.dim1()++, iry.dim1()++)
    00364         {
    00365             //std::cerr << "Y = " << pos[1] << std::endl;
    00366
    00367             for(isx=isy, irx=iry, pos[0]=0; pos[0]<w;
    00368                 pos[0]++, isx.dim0()++, irx.dim0()++)
    00369             {
    00370                 //std::cerr << "X = " << pos[0] << std::endl;
    00371
    00372                 if(*irx == 0)
    00373                 {
    00374                     // find candidate pixels for growing and fill heap
    00375                     for(int i=0; i<directionCount; i++)
    00376                     {
    00377                         cneighbor = *(irx + Neighborhood::diff((Direction)i));
    00378                         if(cneighbor > 0)
    00379                         {
    00380                             CostType cost = stats[cneighbor].cost(as(isx));
    00381
    00382                             Voxel * voxel =
    00383                                 allocator.create(pos, pos+Neighborhood::diff((Direction)i), cost, count++, cneighbor);
    00384                             pheap.push(voxel);
    00385                         }
    00386                     }
    00387                 }
    00388             }
    00389         }
    00390     }
    00391
    00392     // perform region growing
    00393     while(pheap.size() != 0)
    00394     {
    00395         Voxel * voxel = pheap.top();
    00396         pheap.pop();
    00397
    00398         Diff_type pos = voxel->location_;
    00399         Diff_type nearest = voxel->nearest_;
    00400         int lab = voxel->label_;
    00401         CostType cost = voxel->cost_;
    00402
    00403         allocator.dismiss(voxel);
    00404
    00405         if((srgType & StopAtThreshold) != 0 && cost > max_cost)
    00406             break;
    00407
    00408         irx = ir + pos;
    00409         isx = srcul + pos;
    00410
    00411         if(*irx) // already labelled region / watershed?
    00412             continue;
    00413
    00414         if((srgType & KeepContours) != 0)
    00415         {
    00416             for(int i=0; i<directionCount; i++)
    00417             {
    00418                 cneighbor = * (irx + Neighborhood::diff((Direction)i));
    00419                 if((cneighbor>0) && (cneighbor != lab))
    00420                 {
    00421                     lab = SRGWatershedLabel;
    00422                     break;
    00423                 }
    00424             }
    00425         }
    00426
    00427         *irx = lab;
    00428
    00429         if((srgType & KeepContours) == 0 || lab > 0)
    00430         {
    00431             // update statistics
    00432             stats[*irx](as(isx));
    00433
    00434             // search neighborhood
    00435             // second pass: find new candidate pixels
    00436             for(int i=0; i<directionCount; i++)
    00437             {
    00438                 if(*(irx + Neighborhood::diff((Direction)i)) == 0)
    00439                 {
    00440                     CostType cost = stats[lab].cost(as(isx, Neighborhood::diff((Direction)i)));
    00441
    00442                     Voxel * new_voxel =
    00443                         allocator.create(pos+Neighborhood::diff((Direction)i), nearest, cost, count++, lab);
    00444                     pheap.push(new_voxel);
    00445                 }
    00446             }
    00447         }
    00448     }
    00449
    00450     // free temporary memory
    00451     while(pheap.size() != 0)
    00452     {
    00453         allocator.dismiss(pheap.top());
    00454         pheap.pop();
    00455     }
    00456
    00457     // write result
    00458     transformMultiArray(ir, Diff_type(w,h,d), AccessorTraits<int>::default_accessor(),
    00459                         destul, ad, detail::UnlabelWatersheds());
    00460 }
    00461
    00462 template <class SrcImageIterator, class Diff_type, class SrcAccessor,
    00463           class SeedImageIterator, class SeedAccessor,
    00464           class DestImageIterator, class DestAccessor,
    00465           class RegionStatisticsArray, class Neighborhood >
    00466 inline void
    00467 seededRegionGrowing3D(SrcImageIterator srcul, Diff_type shape, SrcAccessor as,
    00468                       SeedImageIterator seedsul, SeedAccessor aseeds,
    00469                       DestImageIterator destul, DestAccessor ad,
    00470                       RegionStatisticsArray & stats, SRGType srgType, Neighborhood n)
    00471 {
    00472     seededRegionGrowing3D( srcul, shape, as, seedsul, aseeds,
    00473                            destul, ad, stats, srgType, n, NumericTraits<double>::max());
    00474 }
    00475
    00476 template <class SrcImageIterator, class Diff_type, class SrcAccessor,
    00477           class SeedImageIterator, class SeedAccessor,
    00478           class DestImageIterator, class DestAccessor,
    00479           class RegionStatisticsArray >
    00480 inline void
    00481 seededRegionGrowing3D(SrcImageIterator srcul, Diff_type shape, SrcAccessor as,
    00482                       SeedImageIterator seedsul, SeedAccessor aseeds,
    00483                       DestImageIterator destul, DestAccessor ad,
    00484                       RegionStatisticsArray & stats, SRGType srgType)
    00485 {
    00486     seededRegionGrowing3D( srcul, shape, as, seedsul, aseeds,
    00487                            destul, ad, stats, srgType, NeighborCode3DSix());
    00488 }
    00489
    00490 template <class SrcImageIterator, class Diff_type, class SrcAccessor,
    00491           class SeedImageIterator, class SeedAccessor,
    00492           class DestImageIterator, class DestAccessor,
    00493           class RegionStatisticsArray >
    00494 inline void
    00495 seededRegionGrowing3D(SrcImageIterator srcul, Diff_type shape, SrcAccessor as,
    00496                       SeedImageIterator seedsul, SeedAccessor aseeds,
    00497                       DestImageIterator destul, DestAccessor ad,
    00498                       RegionStatisticsArray & stats)
    00499 {
    00500     seededRegionGrowing3D( srcul, shape, as, seedsul, aseeds, destul, ad,
    00501                            stats, CompleteGrow);
    00502 }
    00503
    00504 template <class SrcImageIterator, class Shape, class SrcAccessor,
    00505           class SeedImageIterator, class SeedAccessor,
    00506           class DestImageIterator, class DestAccessor,
    00507           class RegionStatisticsArray, class Neighborhood>
    00508 inline void
    00509 seededRegionGrowing3D(triple<SrcImageIterator, Shape, SrcAccessor> img1,
    00510                       pair<SeedImageIterator, SeedAccessor> img3,
    00511                       pair<DestImageIterator, DestAccessor> img4,
    00512                       RegionStatisticsArray & stats,
    00513                       SRGType srgType, Neighborhood n, double max_cost)
    00514 {
    00515     seededRegionGrowing3D(img1.first, img1.second, img1.third,
    00516                           img3.first, img3.second,
    00517                           img4.first, img4.second,
    00518                           stats, srgType, n, max_cost);
    00519 }
    00520
    00521 template <class SrcImageIterator, class Shape, class SrcAccessor,
    00522           class SeedImageIterator, class SeedAccessor,
    00523           class DestImageIterator, class DestAccessor,
    00524           class RegionStatisticsArray, class Neighborhood>
    00525 inline void
    00526 seededRegionGrowing3D(triple<SrcImageIterator, Shape, SrcAccessor> img1,
    00527                       pair<SeedImageIterator, SeedAccessor> img3,
    00528                       pair<DestImageIterator, DestAccessor> img4,
    00529                       RegionStatisticsArray & stats,
    00530                       SRGType srgType, Neighborhood n)
    00531 {
    00532     seededRegionGrowing3D(img1.first, img1.second, img1.third,
    00533                           img3.first, img3.second,
    00534                           img4.first, img4.second,
    00535                           stats, srgType, n, NumericTraits<double>::max());
    00536 }
    00537
    00538 template <class SrcImageIterator, class Shape, class SrcAccessor,
    00539           class SeedImageIterator, class SeedAccessor,
    00540           class DestImageIterator, class DestAccessor,
    00541           class RegionStatisticsArray>
    00542 inline void
    00543 seededRegionGrowing3D(triple<SrcImageIterator, Shape, SrcAccessor> img1,
    00544                       pair<SeedImageIterator, SeedAccessor> img3,
    00545                       pair<DestImageIterator, DestAccessor> img4,
    00546                       RegionStatisticsArray & stats, SRGType srgType)
    00547 {
    00548     seededRegionGrowing3D(img1.first, img1.second, img1.third,
    00549                           img3.first, img3.second,
    00550                           img4.first, img4.second,
    00551                           stats, srgType, NeighborCode3DSix());
    00552 }
    00553
    00554 template <class SrcImageIterator, class Shape, class SrcAccessor,
    00555           class SeedImageIterator, class SeedAccessor,
    00556           class DestImageIterator, class DestAccessor,
    00557           class RegionStatisticsArray>
    00558 inline void
    00559 seededRegionGrowing3D(triple<SrcImageIterator, Shape, SrcAccessor> img1,
    00560                       pair<SeedImageIterator, SeedAccessor> img3,
    00561                       pair<DestImageIterator, DestAccessor> img4,
    00562                       RegionStatisticsArray & stats)
    00563 {
    00564     seededRegionGrowing3D(img1.first, img1.second, img1.third,
    00565                           img3.first, img3.second,
    00566                           img4.first, img4.second,
    00567                           stats);
    00568 }
    00569
    00570 } // namespace vigra
    00571
    00572 #endif // VIGRA_SEEDEDREGIONGROWING_HXX
    00573

© Ullrich Köthe (ullrich.koethe@iwr.uni-heidelberg.de) Heidelberg Collaboratory for Image Processing, University of Heidelberg, Germany | html generated using doxygen and Python vigra 1.9.0 (Tue Nov 6 2012)