学步园

基于opencv的基本的hsv特征提取

可以考虑：

将图像根据其颜色信息进行图像分割成若干region，并将颜色分为多个bin，每个region进行颜色空间量化建立颜色索引，

进而建立二进制图像颜色索引表。为加快查找速度，还可以构造二分查找树进行特征检索。

#include <cv.h>
#include <highgui.h>
#include <iostream>
using namespace std;

int main( int argc, char** argv )
{
	IplImage * src= cvLoadImage("F:\\program files\\VS2010\\MyProjects\\OpenORB\\OpenORB\\src_image\\p001\\frame0001Person02.png",1);
	IplImage* hsv = cvCreateImage( cvGetSize(src), 8, 3 );
	IplImage* h_plane = cvCreateImage( cvGetSize(src), 8, 1 );
	IplImage* s_plane = cvCreateImage( cvGetSize(src), 8, 1 );
	IplImage* v_plane = cvCreateImage( cvGetSize(src), 8, 1 );
	IplImage* planes[] = { h_plane, s_plane };
	/** H 分量划分为16个等级，S分量划分为8个等级*/
	int h_bins = 16, s_bins = 8;
	int hist_size[] = {h_bins, s_bins};
	/** H 分量的变化范围*/
	float h_ranges[] = { 0, 180 };
	/** S 分量的变化范围*/
    float s_ranges[] = { 0, 255 };
	float* ranges[] = { h_ranges, s_ranges }; 
	/** 输入图像转换到HSV颜色空间*/
	cvCvtColor( src, hsv, CV_BGR2HSV );
	cvCvtPixToPlane( hsv, h_plane, s_plane, v_plane, 0 );
	/** 创建直方图，二维, 每个维度上均分*/
	CvHistogram * hist = cvCreateHist( 2, hist_size, CV_HIST_ARRAY, ranges, 1 );
	/** 根据H,S两个平面数据统计直方图*/
	cvCalcHist( planes, hist, 0, 0 );
	/** 获取直方图统计的最大值，用于动态显示直方图*/
	float max_value;
	cvGetMinMaxHistValue( hist, 0, &max_value, 0, 0 );
	/** 设置直方图显示图像*/
	int height = 240;
	int width = (h_bins*s_bins*6);
	IplImage* hist_img = cvCreateImage( cvSize(width,height), 8, 3 );
	cvZero( hist_img );
	/** 用来进行HSV到RGB颜色转换的临时单位图像*/
	IplImage * hsv_color = cvCreateImage(cvSize(1,1),8,3);
	IplImage * rgb_color = cvCreateImage(cvSize(1,1),8,3);
	int bin_w = width / (h_bins * s_bins);
	for(int h = 0; h < h_bins; h++)
	{
		for(int s = 0; s < s_bins; s++)
		{
			int i = h*s_bins + s;
			/** 获得直方图中的统计次数，计算显示在图像中的高度*/
			float bin_val = cvQueryHistValue_2D( hist, h, s );
			int intensity = cvRound(bin_val*height/max_value);
			/** 获得当前直方图代表的颜色，转换成RGB用于绘制*/
			cvSet2D(hsv_color,0,0,cvScalar(h*180.f / h_bins,s*255.f/s_bins,255,0));
			cvCvtColor(hsv_color,rgb_color,CV_HSV2BGR);
			CvScalar color = cvGet2D(rgb_color,0,0);
			cvRectangle( hist_img, cvPoint(i*bin_w,height),
				cvPoint((i+1)*bin_w,height - intensity),
				color, -1, 8, 0 );
		}
	}
	cvNamedWindow( "Source", 1 );
	cvShowImage( "Source", src );
	cvNamedWindow( "H-S Histogram", 1 );
	cvShowImage( "H-S Histogram", hist_img );
	cvWaitKey(0);
}