Opencv之kmeans图像分割

最新推荐文章于 2025-06-11 14:03:40 发布

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最新推荐文章于 2025-06-11 14:03:40 发布

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分类专栏：图像分割 opencv 文章标签： opencv

本文链接：https://blog.youkuaiyun.com/qq_37589971/article/details/106101823

本文详细介绍了如何使用OpenCV库中的KMeans算法进行图像分割，通过实例展示了KMeans在图像处理中的强大功能，包括步骤解析和代码实现。

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int imageSeg_kmeans()
{
	string image_path = "D:/vs2019Proj/ConsoleApplication1/timg.jpg";
	Mat src_image = imread(image_path);
	if (!src_image.data)
	{
		cout << "could not load image.." << endl;
		return -1;
	}
	//颜色板
	vector<Scalar> colorTab = {
		{0,0,255},
		{0,255,0},
		{255,0,0},
		{255,255,0},
		{0,255,255},
		{255,0,255}
	};
	int width = src_image.cols;
	int height = src_image.rows;
	int chnes = src_image.channels();
	//把彩色图像中的数据点提取出来放入points里面
	//points的类型是CV_32F
	Mat points(width * height, chnes, CV_32F,Scalar(10));
	for (int row = 0; row < height; row++)
	{
		uchar* ptr = src_image.ptr<uchar>(row);
		for (int col = 0; col < width* chnes; col+= chnes)
		{
			int index = row * width + col/chnes;
			float* ptr_points = points.ptr<float>(index);
			ptr_points[0] = static_cast<int>(ptr[col]);//B
			ptr_points[1] = static_cast<int>(ptr[col+1]);//G
			ptr_points[2] = static_cast<int>(ptr[col+2]);