C# OpenCvSharp实现去除字母后面的杂线
目录
- 效果
- 项目
- 代码
效果
项目
代码
///php <summary>
/// Applies an adaptive threshold to an array./// </summary>/// <param name="src">Source 8-bit single-channel image.</param>/// <param name="dst">Destination image of the same size and the same type as src .</param>/// <param name="maxValue">Non-zero value assigned to the pixels for which the condition is satisfied. See the details below.</param>/// <param name="adaptiveMethod">Adaptive thresholding algorithm to use, ADAPTIVE_THRESH_MEAN_C or ADAPTIVE_THRESH_GAUSSIAN_C .</param>/// <param name="thresholdType">Thresholding type that must be either THRESH_BINARY or THRESH_BINARY_INV .</param>/// <param name="blockSize">Size of a pixel neighborhood that is used to calculate a threshold value for the pixel: 3, 5, 7, and so on.</param>/// <param name="编程客栈c">Constant subtracted from the mean or weighted mean (see the details below). /// Normally, it is positive but may be zero or negative as well.</param>public static void AdaptiveThreshold(InputArray src, OutputArray dst,double maxValue, AdaptiveThresholdTypes adaptiveMethod, ThresholdTypes thresholdType, int blockSize, double c)
using OpenCvSharp; using System; using System.Drawing; using System.Windows.Forms; namespace OpenCvSharp_Demo { public partial class frmMain : Form { public frmMain() { InitializeComponent(); } string image_path = 编程""; private void Form1_Load(object sender, EventArgs e) { image_path = "1.jpg"; pictureBox1.Image = new Bitmap(image_path); } private void button2_Click(object sender, EventArgs e) { Mat gray = new Mat(image_path, ImreadModes.Grayscale); Mat binary = new Mat(); Cv2.AdaptiveThreshold(~gray, binary, 255, AdaptiveThresholdTypes.MeanC, ThresholdTypes.Binary, 15, -2); Mat kernel = Cv2.GetStructur编程ingElement(MorphShapes.Rect, new OpenCvSharp.Sijavascriptze(4, 4), new OpenCvSharp.Point(-1, -1)); //开运算 Mat dst = new Mat(); Cv2.MorphologyEx(binary, dst, MorphTypes.Open, kernel); pictureBox2.Image = new Bitmap(dst.ToMemoryStream()); } } }
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