FloodFiller.h

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/********************************************************************
**                Image Component Library (ICL)                    **
**                                                                 **
** Copyright (C) 2006-2013 CITEC, University of Bielefeld          **
**                         Neuroinformatics Group                  **
** Website: www.iclcv.org and                                      **
**          http://opensource.cit-ec.de/projects/icl               **
**                                                                 **
** File   : ICLCV/src/ICLCV/FloodFiller.h                          **
** Module : ICLCV                                                  **
** Authors: Christof Elbrechter                                    **
**                                                                 **
**                                                                 **
** GNU LESSER GENERAL PUBLIC LICENSE                               **
** This file may be used under the terms of the GNU Lesser General **
** Public License version 3.0 as published by the                  **
**                                                                 **
** Free Software Foundation and appearing in the file LICENSE.LGPL **
** included in the packaging of this file.  Please review the      **
** following information to ensure the license requirements will   **
** be met: http://www.gnu.org/licenses/lgpl-3.0.txt                **
**                                                                 **
** The development of this software was supported by the           **
** Excellence Cluster EXC 277 Cognitive Interaction Technology.    **
** The Excellence Cluster EXC 277 is a grant of the Deutsche       **
** Forschungsgemeinschaft (DFG) in the context of the German       **
** Excellence Initiative.                                          **
**                                                                 **
********************************************************************/

#pragma once

#include <ICLUtils/CompatMacros.h>
#include <ICLCore/Img.h>

namespace icl{
  namespace cv{
    

    class ICLCV_API FloodFiller{
      std::vector<utils::Point> futurePoints;
      
      utils::Rect prepare(const utils::Size &imageSize, const utils::Point &seed);
  
      public:
  
      struct ICLCV_API Result{
        std::vector<utils::Point> pixels; 
        core::Img8u ffLUT;               
      } result;
      

      const Result &apply(const core::ImgBase *image, const utils::Point &seed, double referenceValue, double threshold);
  
      

      const Result &applyColor(const core::ImgBase *image, const utils::Point &seed, 
                          double refR, double refG, double refB, double threshold);
      

      template<class T, class Criterion>
      inline const Result &applyGeneric(const core::Img<T> &image, const utils::Point &seed, Criterion crit){
        utils::Rect r = prepare(image.getSize(),seed);
        
        utils::Point *n = futurePoints.data(); // next point to seed from
        utils::Point *e = n;                   // end of stored seed points
        
        *e++ = seed;
        
        const core::Channel<T> im = image[0];
        core::Channel8u ff = result.ffLUT[0];
        
        ff(seed.x,seed.y) = 255;
  
        while(n != e){
          const int x = n->x;
          const int y = n->y;
          ++n;
          if(crit(im(x,y))){
            result.pixels.push_back(utils::Point(x,y));
  #define ICL_DYNAMIC_FLOOD_FILLER_P(x,y)                                 \
            if(r.contains(x,y) && !ff(x,y)){                              \
              *e++ = utils::Point(x,y);                                          \
              ff(x,y) = 255;                                              \
            }
            
            ICL_DYNAMIC_FLOOD_FILLER_P(x-1,y-1); 
            ICL_DYNAMIC_FLOOD_FILLER_P(x,y-1); 
            ICL_DYNAMIC_FLOOD_FILLER_P(x+1,y-1);
            
            ICL_DYNAMIC_FLOOD_FILLER_P(x-1,y);
            ICL_DYNAMIC_FLOOD_FILLER_P(x+1,y);
            
            ICL_DYNAMIC_FLOOD_FILLER_P(x-1,y+1); 
            ICL_DYNAMIC_FLOOD_FILLER_P(x,y+1); 
            ICL_DYNAMIC_FLOOD_FILLER_P(x+1,y+1);
  #undef ICL_DYNAMIC_FLOOD_FILLER_P
          }
        }
        return result;
      }
  

      template<class T, class Criterion3Channels>
      inline const Result &applyColorGeneric(const core::Img<T> &image, const utils::Point &seed, Criterion3Channels crit){
        utils::Rect r = prepare(image.getSize(),seed);
        
        utils::Point *n = futurePoints.data(); // next point to seed from
        utils::Point *e = n;                   // end of stored seed points
        
        *e++ = seed;
        
        const core::Channel<T> im0 = image[0];
        const core::Channel<T> im1 = image[1];
        const core::Channel<T> im2 = image[2];
  
        core::Channel8u ff = result.ffLUT[0];
        
        ff(seed.x,seed.y) = 255;
  
        while(n != e){
          const int x = n->x;
          const int y = n->y;
          ++n;
          if(crit(im0(x,y),im1(x,y),im2(x,y))){
            result.pixels.push_back(utils::Point(x,y));
  #define ICL_DYNAMIC_FLOOD_FILLER_P(x,y)                                 \
            if(r.contains(x,y) && !ff(x,y)){                              \
              *e++ = utils::Point(x,y);                                          \
              ff(x,y) = 255;                                              \
            }
            
            ICL_DYNAMIC_FLOOD_FILLER_P(x-1,y-1); 
            ICL_DYNAMIC_FLOOD_FILLER_P(x,y-1); 
            ICL_DYNAMIC_FLOOD_FILLER_P(x+1,y-1);
            
            ICL_DYNAMIC_FLOOD_FILLER_P(x-1,y);
            ICL_DYNAMIC_FLOOD_FILLER_P(x+1,y);
            
            ICL_DYNAMIC_FLOOD_FILLER_P(x-1,y+1); 
            ICL_DYNAMIC_FLOOD_FILLER_P(x,y+1); 
            ICL_DYNAMIC_FLOOD_FILLER_P(x+1,y+1);
  #undef ICL_DYNAMIC_FLOOD_FILLER_P
          }
        }
        return result;
      }
  
      template<class T>
      struct DefaultCriterion{
        T val;
        T thresh;
        inline DefaultCriterion(T val, T thresh):val(val),thresh(thresh){}
        inline bool operator()(const T &pix) const{
          return ::abs(val-pix) < thresh;
        }
      };
  
      template<class T>
      struct ReferenceColorCriterion{
        T refcol[3];
        T maxSquaredEuklDist;
        
        inline ReferenceColorCriterion(T refr, T refg, T refb, T maxEuclDist):
          maxSquaredEuklDist(maxEuclDist*maxEuclDist){
          refcol[0] = refr;
          refcol[1] = refg;
          refcol[2] = refb;
        }
        inline bool operator()( const T &r, const T &g, const T &b) const{
          return utils::sqr(r-refcol[0]) + utils::sqr(g-refcol[1]) + utils::sqr(b-refcol[2])  < maxSquaredEuklDist;
        }
      };
    };
  
    // specialized
    template<>
    struct FloodFiller::ReferenceColorCriterion<icl8u>{
      int refcol[3];
      int maxSquaredEuklDist;
      
      inline ReferenceColorCriterion(icl8u refr, icl8u refg, icl8u refb, int maxEuclDist):
      maxSquaredEuklDist(maxEuclDist*maxEuclDist){
        refcol[0] = refr;
        refcol[1] = refg;
        refcol[2] = refb;
      }
      inline bool operator()( const icl8u &r, const icl8u &g, const icl8u &b) const{
        return utils::sqr(int(r)-refcol[0]) + utils::sqr(int(g)-refcol[1]) + utils::sqr(int(b)-refcol[2]) < maxSquaredEuklDist;
      }
    };
  } // namespace cv
}