www.pudn.com > DetectSharpAVI.rar > DetectSharp.cpp

#include "stdafx.h" 
#include  
#include  
#include  
 
struct SharpPrarm 
{ 
	unsigned int rbgcount;      //当前rbg平均距离 
	unsigned int sharpcount;      //当前清晰值 
        int rgbencroach;   //当前rbg平均距离与阈值差值 
        int sharpencroach;   //当前清晰值与阈值差值 
	bool  warnning;          //是否发出警告 
	bool  sharp;            //清晰true 不清晰false   
}; 
 
 
SharpPrarm DetectSharp(IplImage *Img, int RGBThreshold ,int GrayThreshold); 
int DetectBlurRGB(IplImage *Img);   //用颜色之间的距离 
int DetectGray(IplImage *GaryImg);    //用平方梯度函数 
int DetectBlur(IplImage *GrayImg,int x,int y,int width, int hight); 
 
/*********************************************************************** 
检测函数： 
参数：彩色图像， 颜色距离阈值，清晰度阈值 
返回值：返回值为SharpPrarm结构体，计算出的阈值都大于给定阈值清晰图像，否则阈值模糊图像 
阈值视频帧尺寸和场景有关系。 
***********************************************************************/ 
SharpPrarm DetectSharp(IplImage *Img, int RGBThreshold =15,int GrayThreshold =180) 
{ 
	SharpPrarm MyParam; 
	IplImage *GrayImg = cvCreateImage(cvGetSize(Img), 8, 1); 
 
	cvCvtColor(Img, GrayImg, CV_BGR2GRAY); 
     
	int nrgb = DetectBlurRGB(Img); 
	int ngray = DetectGray(GrayImg); 
 
 
	if (nrgbwidth/3, GrayImg->height/3) )+ 
					          (unsigned int)(0.19*DetectBlur(GrayImg, GrayImg->width*2/3, 0, GrayImg->width, GrayImg->height/3))+ 
							  (unsigned int)(0.24*DetectBlur(GrayImg, GrayImg->width/3, GrayImg->height/3, GrayImg->width*2/3, GrayImg->height*2/3))+ 
							  (unsigned int)(0.19*DetectBlur(GrayImg, 0, GrayImg->height*2/3, GrayImg->width/3, GrayImg->height))+ 
							  (unsigned int)(0.19*DetectBlur(GrayImg, GrayImg->width*2/3, GrayImg->height*2/3, GrayImg->width, GrayImg->height)); 
 
		    return nCountSharp; 
} 
 
 
 
int DetectBlur(IplImage *GrayImg,int x,int y,int width, int hight) 
{ 
	double sharp =0, 
		temp; 
	CvScalar s1,s2; 
 
	for(int i=y; iheight-1; 
	int width = Img->width; 
 
	for(int i=0; i