C# OpenCvSharp 去除字母后面的杂线

目录

效果

项目

代码

下载

---

效果

项目

代码

///

/// Applies an adaptive threshold to an array.
///

/// Source 8-bit single-channel image.
/// Destination image of the same size and the same type as src .
/// Non-zero value assigned to the pixels for which the condition is satisfied. See the details below.
/// Adaptive thresholding algorithm to use, ADAPTIVE_THRESH_MEAN_C or ADAPTIVE_THRESH_GAUSSIAN_C .
/// Thresholding type that must be either THRESH_BINARY or THRESH_BINARY_INV .
/// Size of a pixel neighborhood that is used to calculate a threshold value for the pixel: 3, 5, 7, and so on.
/// Constant subtracted from the mean or weighted mean (see the details below). 
/// Normally, it is positive but may be zero or negative as well.
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 = "";
 
        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.GetStructuringElement(MorphShapes.Rect, new OpenCvSharp.Size(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());
 
        }
 
    }
}

下载

Demo下载