opencv dots_image_kernel

1,opencv dots_image_kernel 

// halcon dots_image kernel估算（d=5)
cv::Mat getDotKernel(int d = 5){
	// 保证d为正的奇数
	d |= 0x01;

	cv::Mat kernel = cv::Mat::zeros(d + 2, d + 2, CV_8UC1);
	int cx = kernel.cols / 2;
	int cy = kernel.rows / 2;
	int cnt255 = 0, cnt128 = 0, cnt0 = 0;
	for (int row = 0; row < kernel.rows; ++row) {
		for (int col = 0; col < kernel.cols; ++col)	{
			float dis = std::sqrt(std::pow(col - cx, 2) + std::pow(row - cy, 2));
			if (dis < d / 2.0){
				kernel.at(row, col) = 255;
				cnt255++;
			}
			else if (dis < d / 2.0 + 1.0){
				kernel.at(row, col) = 128;
				cnt128++;
			}
			else {
				kernel.at(row, col) = 0;
				cnt0++;
			}
		}
	}
	//
	cv::imwrite("kernel8u.0.png", kernel);
	//
	for (int row = 0; row < kernel.rows; ++row) {
		for (int col = 0; col < kernel.cols; ++col){
			switch (kernel.at(row, col))
			{
			case 255:
				kernel.at(row, col) = cnt128;
				break;
			case 128:
				kernel.at(row, col) = -cnt255;
			default:
				break;
			}
		}
	}
	cv::imwrite("kernel8u.1.png", kernel);
	//
	if (cnt255 *cnt128){
		kernel.convertTo(kernel, CV_32F, 1.0 / (cnt255*cnt128));
	}
	
	return kernel;
}

2,单元测试

3，结果