OpenCV--041:Triangle二值寻找算法

程序员文章站 2024-02-20 23:34:22

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三角形的二值化法：

不用自己指定thresh值，系统会进行计算并且作为返回值返回。

THRESH_OTSU最适用于双波峰。
THRESH_TRIANGLE最适用于单个波峰，最开始用于医学分割细胞等。

原理：
1.图像转灰度
2.计算图像灰度直方图
3.寻找直方图中两侧边界
4.寻找直方图最大值
5.检测是否最大波峰在亮的一侧，否则翻转
6.计算阈值得到阈值T,如果翻转则255-T

void Threshold(Mat& src, Mat& dst, double thresh) {
	int bt;
	//遍历灰度图像，统计灰度级的个数
	for (int i = 0; i < src.rows; i++)
	{
		uchar* p = src.ptr<uchar>(i);
		uchar* p1 = dst.ptr<uchar>(i);
		for (int j = 0; j < src.cols; j++)
		{
		    bt = p[j];
			cout << "bt=" << bt << " ";
			if (bt > thresh) {
				bt = 255;
			}
			else {
				bt = 0;
			}
			p1[j] = bt;

		
		}
	}
	imshow("src", src);
	imshow("dst", dst);
}


void Triangle(Mat& src, Mat& dst) {

	int i = 0, j = 0;
	int gray;
	int temp = 0;
	bool isflipped = false;

	//求直方图
	//void calcHist( const Mat* images, int nimages,
	//                const int* channels, InputArray mask,
	//	            OutputArray hist, int dims, const int* histSize,
	//	            const float** ranges, bool uniform = true, bool accumulate = false );
	//
	/*int nimages = 1;
	int channels[1] = { 0 };
	Mat calchist;
	int dims = 1;

	int histSize[1] = { 256 };
	//每一维数值的取值范围ranges
	float hranges[2] = { 0,255 };
	//每一维数值的取值范围
	const float* ranges[1] = { hranges };
	//灰度级别

	calcHist(&src, nimages, channels, Mat(), calchist, dims, histSize, ranges);
	*/

	int calchist[256] = { 0 };
	//遍历灰度图像，统计灰度级的个数
	for (i = 0; i < src.rows; i++)
	{
		uchar* p = src.ptr<uchar>(i);
		for (j = 0; j < src.cols; j++)
		{
			int value = p[j];
			calchist[value]++;
		}
	}
	
	
	//寻找直方图中两侧边界
	int left_bound = 0;
	int right_bound = 0;
	int max = 0;
	int max_index = 0;

	//左侧为零的位置
	for (i = 0; i < 256; i++) {
		if (calchist[i] > 0) {
			left_bound = i;
			break;
		}
	}
	//直方图为零的位置
	if (left_bound > 0) {
		left_bound--;
	}

	//直方图右侧为零的位置
	for (i = 255; i > 0; i--) {
		if (calchist[i] > 0) {
			right_bound = i;
			break;
		}
	}

	//直方图为零的地方
	if (right_bound > 0) {
		right_bound++;
	}

	//寻找直方图最大值
	for (i = 0; i < 256; i++) {
		if (calchist[i] > max) {
			max = calchist[i];
			max_index = i;
		}
	}

	//判断最大值是否在最左侧，如果是则不用翻转
	//因为三角形二值化只能适用于最大值在最右侧
	if (max_index - left_bound < right_bound - max_index) {
		isflipped = true;
		i = 0;
		j = 255;
		while (i < j) {
			//左右交换
			temp = calchist[i];
			calchist[i] = calchist[j];
			calchist[j] = temp;
			i++;
			j--;
		}
		left_bound = 255 - right_bound;
		max_index = 255 - max_index;

	}

	//求阈值
	double thresh = left_bound;
	double a, b, dist = 0, tempdist;
	a = max;
	b = left_bound - max_index;
	for (int i = left_bound+1; i <= max_index; i++)
	{
		//计算距离--不需要真正计算
		tempdist = a * i + b * calchist[i];
		if (tempdist > dist) {
			dist = tempdist;
			thresh = i;
		}
	}
	thresh--;

	// 对已经得到的阈值T,如果前面已经翻转了，则阈值要用255-T
	if (isflipped)
	{
		thresh = 255 - thresh;
	}

	//二值化
	Threshold(image, dst, thresh);
	
    

}

int main() {
	Mat src = imread("D:/test/src.jpg", 0);
	Mat dst;
	//threshold(src, dst, 0, 255, THRESH_BINARY | THRESH_OTSU);

	Triangle(src, dst);

	
	waitKey(0);
	return 0;




}