Opencv2.4学习：：二值化（3）自适应二值化

二值化系列：

（1）OTSU算法

（2）固定二值化

（3）自适应二值化

 

adaptiveThreshold

void adaptiveThreshold(InputArray src, OutputArraydst,double maxValue，int adaptiveMethod,int thresholdType,

int blockSize,double C );

• double maxValue-----------------------//灰度图像的最大值，最小值为0(即黑色)
• int adaptiveMethod-------------------//阈值算法CV_ADAPTIVE_THRESH_MEAN_C、CV_ADAPTIVE_THRESH_GAUSSIAN_C
• int thresholdType---------------------//二值图是否反转CV_THRESH_BINARY、CV_THRESH_BINARY_INV
• int blockSize---------------------------//块的大小，只能取奇数3,5,7......
• double C-------------------------------//加权系数，可取负数

调用实例： 

#include
#include
#include
using namespace std;
using namespace cv;
int main()
{
	Mat srcImage = imread("F:\\opencv_re_learn\\2.jpg");
	if (!srcImage.data){
		cout << "failed to read" << endl;
		system("pause");
		return -1;
	}
	imshow("src", srcImage);
	//conver to gray
	Mat srcGray;
	cvtColor(srcImage, srcGray, CV_BGR2GRAY);
	Mat dstImage;
	//初始化参数
	int blockSize = 3;
	int constValue = 5;
	const int maxVal = 255;
	//算法选择
	//0:ADAPTIVE_THRESH_MEAN_C
	//1:ADAPTIVE_THRESH_GAUSSIAN_C
	//阈值类型
	//0:THRESH_BINARY
	//1:THRESH_BINARY_INV

	//阈值化
	adaptiveThreshold(srcGray, dstImage, maxVal,
		ADAPTIVE_THRESH_GAUSSIAN_C, THRESH_BINARY,
		blockSize, constValue);
	imshow("thres_result", dstImage);
	waitKey(0);
	return 0;
}

 实现效果：