【opencv】LBP特征提取

void elbp(Mat& src, Mat &dst, int radius, int neighbors)
{
 
	for (int n = 0; n < neighbors; n++)
	{
		// 采样点的计算
		float x = static_cast<float>(-radius * sin(2.0*CV_PI*n / static_cast<float>(neighbors)));
		float y = static_cast<float>(radius * cos(2.0*CV_PI*n / static_cast<float>(neighbors)));
		// 上取整和下取整的值
		int fx = static_cast<int>(floor(x));
		int fy = static_cast<int>(floor(y));
		int cx = static_cast<int>(ceil(x));
		int cy = static_cast<int>(ceil(y));
		// 小数部分
		float ty = y - fy;
		float tx = x - fx;
		// 设置插值权重
		float w1 = (1 - tx) * (1 - ty);
		float w2 = tx  * (1 - ty);
		float w3 = (1 - tx) *      ty;
		float w4 = tx  *      ty;
		// 循环处理图像数据
		for (int i = radius; i < src.rows - radius; i++)
		{
			for (int j = radius; j < src.cols - radius; j++)
			{
				// 计算插值
				float t = static_cast<float>(w1*src.at<uchar>(i + fy, j + fx) + w2*src.at<uchar>(i + fy, j + cx) + w3*src.at<uchar>(i + cy, j + fx) + w4*src.at<uchar>(i + cy, j + cx));
				// 进行编码
				dst.at<uchar>(i - radius, j - radius) += ((t > src.at<uchar>(i, j)) || (std::abs(t - src.at<uchar>(i, j)) < std::numeric_limits<float>::epsilon())) << n;
			}
		}
	}
}
 
void elbp1(Mat& src, Mat &dst)
{
 
	// 循环处理图像数据
	for (int i = 1; i < src.rows - 1; i++)
	{
		for (int j = 1; j < src.cols - 1; j++)
		{
			uchar tt = 0;
			int tt1 = 0;
			uchar u = src.at<uchar>(i, j);
			if (src.at<uchar>(i - 1, j - 1)>u) { tt += 1 << tt1; }
			tt1++;
			if (src.at<uchar>(i - 1, j)>u) { tt += 1 << tt1; }
			tt1++;
			if (src.at<uchar>(i - 1, j + 1) > u) { tt += 1 << tt1; }
			tt1++;
			if (src.at<uchar>(i, j + 1) > u) { tt += 1 << tt1; }
			tt1++;
			if (src.at<uchar>(i + 1, j + 1) > u) { tt += 1 << tt1; }
			tt1++;
			if (src.at<uchar>(i + 1, j) > u) { tt += 1 << tt1; }
			tt1++;
			if (src.at<uchar>(i + 1, j - 1) > u) { tt += 1 << tt1; }
			tt1++;
			if (src.at<uchar>(i - 1, j) > u) { tt += 1 << tt1; }
			tt1++;
 
			dst.at<uchar>(i - 1, j - 1) = tt;
		}
	}
}