mycolorfeature.cpp

这是一个分水岭程序

// MyColorFeature.cpp: implementation of the MyColorFeature class.
//
//////////////////////////////////////////////////////////////////////

#include "stdafx.h"
#include "myimagedb.h"
#include "MyColorFeature.h"
#include "mycolorspace.h"
#include <MATH.H>

#ifdef _DEBUG
#undef THIS_FILE
static char THIS_FILE[]=__FILE__;
#define new DEBUG_NEW
#endif

//////////////////////////////////////////////////////////////////////
// Construction/Destruction
//////////////////////////////////////////////////////////////////////

MyColorFeature::MyColorFeature()
{

}

MyColorFeature::~MyColorFeature()
{

}

D1ColorBin* MyColorFeature::CalcuHisD1(BYTE* rgbData, INT width, INT height)
//计算一维直方图，来自RemoteDemo;
//输入参数无需预分配内存;
{
	unsigned long imglen = width*height;

	MyHSV* myhsvbuf = new MyHSV[imglen];
	HsvBelongTo* imgd1data = new HsvBelongTo[imglen];

	int i,j;
	unsigned long pos;
	myColorSpace.RgbtoHsv(rgbData, width, height, myhsvbuf);

	for(i=0;i<height;i++)
	{
		for (j=0;j<width;j++)
		{
			pos = i*width+j;
			imgd1data[pos].hsv.h = myhsvbuf[pos].h;
			imgd1data[pos].hsv.s = myhsvbuf[pos].s;
			imgd1data[pos].hsv.v = myhsvbuf[pos].v;
			imgd1data[pos].belongto = 0;
		}
	}
	delete [] myhsvbuf;

	//以下设定初始色彩薄
	D1ColorBinUnit* mycolorbook = new D1ColorBinUnit[CBDIM];
    D1ColorBinUnit* newcolorbook = new D1ColorBinUnit[CBDIM];//备份，互相交换；

	int n;
	for(n=0; n<CBDIM; n++)
	{
		if( ( n % 9 ) % 3 == 0){mycolorbook[n].hsv.v = 0.0;}
		if( ( n % 9 ) % 3 == 1) {mycolorbook[n].hsv.v = (FLOAT)0.2;}
		if( ( n % 9 ) % 3 == 2) {mycolorbook[n].hsv.v = (FLOAT)0.7;}
		if( ( n % 9 )  / 3 == 0) {mycolorbook[n].hsv.s = (FLOAT)0.0;}
		if( ( n % 9 )  / 3 == 1) {mycolorbook[n].hsv.s = (FLOAT)0.2;}
		if( ( n % 9 )  / 3 == 2) {mycolorbook[n].hsv.s = (FLOAT)0.7;}
		if(n / 9 == 0) { mycolorbook[n].hsv.h = (FLOAT)(2.0 * PI * 20.0 / 360.0); }
		if(n / 9 == 1) { mycolorbook[n].hsv.h = (FLOAT)(2.0 * PI * 40.0 / 360.0); }
		if(n / 9 == 2) { mycolorbook[n].hsv.h = (FLOAT)(2.0 * PI * 75.0 / 360.0); }
		if(n / 9 == 3) { mycolorbook[n].hsv.h = (FLOAT)(2.0 * PI * 155.0 / 360.0); }
		if(n / 9 == 4) { mycolorbook[n].hsv.h = (FLOAT)(2.0 * PI * 190.0 / 360.0); }
		if(n / 9 == 5) { mycolorbook[n].hsv.h = (FLOAT)(2.0 * PI * 270.0 / 360.0); }
		if(n / 9 == 6) { mycolorbook[n].hsv.h = (FLOAT)(2.0 * PI * 295.0 / 360.0); }
		if(n / 9 == 7) { mycolorbook[n].hsv.h = (FLOAT)(2.0 * PI * 315.0 / 360.0); }
		mycolorbook[n].count = 0;
	}

	//以下对一维色彩空间进行聚类
	double mydis;
	int k,c;
	double dmold = 0;
	double dmnew = 0;
	double tempdis;
	do{
		for (i=0; i<height; i++)
		{
			for (j=0; j<width; j++)
			{
				pos = i*width + j;
				mydis = 10.0;

				for (k=0; k<CBDIM; k++)
				{
					tempdis = myColorSpace.GetHsvDistance(
						mycolorbook[k].hsv, imgd1data[pos].hsv);
					if (tempdis < mydis)
					{
						mydis = tempdis;
						imgd1data[pos].belongto = k;
					}
				}

				c = imgd1data[pos].belongto;
				mycolorbook[c].count ++;
			}
		}
		//完成对像素所属色彩薄及色彩薄颜色个个数的统计

		//下面计算新色彩薄的色彩值和频数
		for(k=0; k<CBDIM; k++)
		{
			if ( mycolorbook[k].count!=0 )
			{
				newcolorbook[k].hsv.h = 0;
				newcolorbook[k].hsv.s = 0;
				newcolorbook[k].hsv.v = 0;
			}else{
				newcolorbook[k].hsv.h = mycolorbook[k].hsv.h;
				newcolorbook[k].hsv.s = mycolorbook[k].hsv.s;
				newcolorbook[k].hsv.v = mycolorbook[k].hsv.v;
			}
			newcolorbook[k].count = mycolorbook[k].count;
		}

		for (i=0; i<height; i++)
		{
			for (j=0; j<width; j++)
			{
				pos = i*width+j;
				c = imgd1data[pos].belongto;
				newcolorbook[c].hsv.h += imgd1data[pos].hsv.h;
				newcolorbook[c].hsv.s += imgd1data[pos].hsv.s;
				newcolorbook[c].hsv.v += imgd1data[pos].hsv.v;
				newcolorbook[c].count ++;
			}
		}
		
		for (k=0; k<CBDIM; k++)
		{
			if (newcolorbook[k].count!=0)
			{
				newcolorbook[k].hsv.h = newcolorbook[k].hsv.h / newcolorbook[k].count;
				newcolorbook[k].hsv.s = newcolorbook[k].hsv.s / newcolorbook[k].count;
				newcolorbook[k].hsv.v = newcolorbook[k].hsv.h / newcolorbook[k].count;
			}			
			mycolorbook[k].hsv.h = newcolorbook[k].hsv.h;
			mycolorbook[k].hsv.s = newcolorbook[k].hsv.s;
			mycolorbook[k].hsv.v = newcolorbook[k].hsv.v;
			mycolorbook[k].count = 0;			
		}
		//至此新的聚类完成,并以新聚类代替旧类，准备下一次迭代

		//以下计算聚类误差
		dmold = dmnew;
		dmnew = 0;

		for (i=0; i<height; i++) 
		{
			for (j=0; j<width; j++)
			{
				pos = i*width+j;
				c = imgd1data[pos].belongto;
				tempdis = myColorSpace.GetHsvDistance(imgd1data[pos].hsv, newcolorbook[c].hsv);
				tempdis = pow(tempdis,2.0) / sqrt(5.0);

				dmnew += tempdis / imglen;
			}
		}
	}while( fabs(dmnew-dmold) > 0.1 );

	for (k=0; k<CBDIM; k++)
	{
		newcolorbook[k].count = newcolorbook[k].count / (FLOAT)imglen;
	}
	//将直方图归一化

	delete [] mycolorbook;
	delete [] imgd1data;
	//单副图像的一维直方图特征已经计算完毕，特征值存储在m_newcolorbook中，
	//newcolorbook中的元素个数现为CBDIM，

	//将得到的直方图存入直方图结构；
	D1ColorBin* toreturn = new D1ColorBin;
	toreturn->bincount = CBDIM;
	toreturn->binunits = newcolorbook;
	return toreturn;
}

DOUBLE MyColorFeature::GetHisD1Distance(D1ColorBin* myhisd1, D1ColorBin* myhisd2)
//计算直方图距离；
{
	//来自RemoteDemo;

	DOUBLE hisd1dis = 0;
	DOUBLE test1 = 0;
	DOUBLE test2 = 0;
	INT count = myhisd1->bincount;
	INT i;

	//测试直方图；
	for (i=0; i<count; i++)
	{
		test1 += myhisd1->binunits[i].count;
		test2 += myhisd2->binunits[i].count;
	}
	if (fabs(test1)>1.000001 || fabs(test2)>1.000001)
	{
		MessageBox(NULL,"","直方图数据有误",MB_OK);
	}	

	//计算距离
	for( i=0; i<count; i++)
	{
		FLOAT sum = myhisd1->binunits[i].count - myhisd2->binunits[i].count;
		hisd1dis += pow(sum, 2.0);
	}	
	hisd1dis = sqrt(hisd1dis);
	hisd1dis = hisd1dis / sqrt(2.0);
	
	return hisd1dis;	
}