OpenCV根据颜色的车牌定位

使用颜色属性：

		for(i=1;i<srcImage.rows;i++)
			for(j=1;j<srcImage.cols-1;j++)
			{
				srcImage.at<uchar>(i,j)=srcImage.at<uchar>(i,j+1)-srcImage.at<uchar>(i,j);

			}

			threshold(srcImage,srcImage,127, 255,CV_THRESH_BINARY_INV);//通过二值化的方式来取反。
			//erode(srcImage,srcImage,Mat(5,5,CV_8U),Point(-1,-1),2);  //腐蚀
			//	dilate(src,src,Mat(5,5,CV_8U),Point(-1,-1),2); //膨胀
			//	morphologyEx(src,src,MORPH_OPEN,Mat(3,3,CV_8U),Point(-1,-1),1);   //开运算
			//	 morphologyEx(src,src,MORPH_CLOSE,Mat(3,3,CV_8U),Point(-1,-1),1);  //闭运算
			erode(srcImage,srcImage,Mat(3,3,CV_8U),Point(-1,-1),5);
			threshold(srcImage,srcImage,127,255,CV_THRESH_BINARY_INV);
			imshow("a",srcImage);
			vector<vector<Point> > contours;
			vector<Vec4i> hierarchy;
			findContours(srcImage, contours, hierarchy, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE, Point(0, 0) );
			Scalar color = Scalar( rng.uniform(0, 255), rng.uniform(0,255), rng.uniform(0,255) );
			for( int i = 0; i < contours.size(); i++ )
			{  
				//使用边界框的方式  
				CvRect aRect =  boundingRect(contours[i]);
				int tmparea=aRect.height*aRect.height;  
				if (((double)aRect.width/(double)aRect.height>2)&& ((double)aRect.width/(double)aRect.height<6)&& tmparea>=2000&&tmparea<=25000)  
				{  
					rectangle(srcShowImage,cvPoint(aRect.x,aRect.y),cvPoint(aRect.x+aRect.width ,aRect.y+aRect.height),color,2);  
					//cvDrawContours( dst, contours, color, color, -1, 1, 8 );  
				}  
			} 


			imshow("da",srcShowImage);

效果例如以下：

颜色能够考虑更仔细，或者考虑在其它颜色空间内实现。