Emgu 学习笔记（二）---图像二值化，自适应阈值化，Otsu二值化

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图像二值化，自适应阈值化，Otsu二值化

Emgu灰度化、二值化操作方法和OpenCV中区别不大，Threshold()来实现的。

自适应阈值是整幅图像使用一个阈值，自适应阈值是图像的不同区域使用不同的阈值，而这个阈值是对整个区域计算出来的。在Emgu中也是调用函数AdaptiveThreshold()来实现的。

public static AdaptiveThreshold(IInputArray src,IOutputArray dst,double maxValue,AdaptiveThresholdType adativeType,ThresholdType thresholdType,int blockSize,double param1)

AdaptiveThresholdType adativeType:自适应阈值计算方法：MeanC和GaussianC

ThresholdType thresholdType：必须为二值化阈值化或者是反二值化阈值化（Binary/BinaryInv）

int blockSize:计算使用的区域矩阵大小：3，5，7，9

来看代码实现：

using System;using System.Collections.Generic;using System.ComponentModel;using System.Data;using System.Drawing;using System.Linq;using System.Text;using System.Threading.Tasks;using System.Windows.Forms;using Emgu.CV;using Emgu.CV.Structure;using Emgu.Util;using Emgu.CV.CvEnum;namespace 全局阈值{    public partial class Form1 : Form    {        public Form1()        {            InitializeComponent();        }        private void Form1_Load(object sender, EventArgs e)        {            Image<Bgr, Byte> image = new Image<Bgr, Byte>(Properties.Resources._2);            pictureBox1.Image = image.ToBitmap();        }        private void button1_Click(object sender, EventArgs e)        {            using (var image = new Image<Bgr, Byte>(Properties.Resources._2))            {                var grayImage = image.Convert<Gray, Byte>();                               pictureBox1.Image = grayImage.ToBitmap();                           }        }        private void button2_Click(object sender, EventArgs e)        {            Image<Bgr, Byte> image = new Image<Bgr, Byte>(Properties.Resources._2);            var grayImage = image.Convert<Gray, Byte>();            var threshImage = grayImage.CopyBlank();            CvInvoke.Threshold(grayImage, threshImage, 150, 255, ThresholdType.Binary);            pictureBox2.Image = threshImage.ToBitmap();        }        private void button3_Click(object sender, EventArgs e)        {            var grayImage = new Image<Gray, Byte>(Properties.Resources._2);            var threshImage = grayImage.ThresholdAdaptive(new Gray(255), AdaptiveThresholdType.MeanC, ThresholdType.Binary, 9, new Gray(5));            pictureBox3.Image = threshImage.ToBitmap();        }        private void button4_Click(object sender, EventArgs e)        {            var grayImage = new Image<Gray, Byte>(Properties.Resources._2);            var threshImge = grayImage.CopyBlank();            CvInvoke.Threshold(grayImage, threshImge, 0, 255, ThresholdType.Otsu);            pictureBox4.Image = threshImge.ToBitmap();        }    }}

效果图：

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