C# OpenCvSharp 基于直线检测的文本图像倾斜校正

效果

代码

using System;
using System.Collections.Generic;
using System.ComponentModel;
using System.Data;
using System.Drawing;
using System.Linq;
using System.Text;
using System.Windows.Forms;
using OpenCvSharp;
 
namespace OpenCvSharp_基于直线检测的文本图像倾斜校正
{
    public partial class Form1 : Form
    {
        public Form1()
        {
            InitializeComponent();
        }
 
        private void button1_Click(object sender, EventArgs e)
        {
            string path = "1.jpg";
 
            pictureBox1.Image = new Bitmap(path);
            Mat mat = new Mat(path);
 
            Mat gray = new Mat(path, ImreadModes.Grayscale);
 
            Mat binary = new Mat();
            Cv2.Threshold(gray, binary, 50, 255, ThresholdTypes.BinaryInv);
 
            Mat element = Cv2.GetStructuringElement(MorphShapes.Rect, new OpenCvSharp.Size(7, 1));
 
            Mat dilation = new Mat();
            Cv2.Dilate(binary, dilation, element);
 
            Mat cannyDst = new Mat();
            Cv2.Canny(dilation, cannyDst, 150, 200);
 
            Mat houghDst = new Mat();
            mat.CopyTo(houghDst);
 
            LineSegmentPolar[] lineing = Cv2.HoughLines(cannyDst, 1, Cv2.PI / 180, 110, 0, 0);
            Scalar color = new Scalar(0, 255, 255);
 
            double meanAngle = 0.0;
            int numCnt = 0;
 
            for (int i = 0; i < lineing.Length; i++)
            {
                double rho = lineing[i].Rho;//线长
                double theta = lineing[i].Theta;//角度
 
                OpenCvSharp.Point pt1 = new OpenCvSharp.Point();
                OpenCvSharp.Point pt2 = new OpenCvSharp.Point();
                double a = Math.Cos(theta);
                double b = Math.Sin(theta);
                double x0 = a * rho, y0 = b * rho;
 
                pt1.X = (int)Math.Round(x0 + 600 * (-b));
                pt1.Y = (int)Math.Round(y0 + 600 * a);
                pt2.X = (int)Math.Round(x0 - 600 * (-b));
                pt2.Y = (int)Math.Round(y0 - 600 * a);
 
                Cv2.Line(houghDst, pt1, pt2, color, 1, LineTypes.Link4);
 
                theta = theta * 180 / Cv2.PI - 90;
 
                meanAngle += theta;
                numCnt++;
            }
            //Cv2.ImShow("houghDst", houghDst);
 
            meanAngle /= numCnt;
            Point2f center = new Point2f(mat.Cols / 2.0f, mat.Rows / 2.0f);
 
            Mat warpDst = new Mat();
            Mat rot_mat = Cv2.GetRotationMatrix2D(center, meanAngle, 1.0);
            OpenCvSharp.Size dst_sz = new OpenCvSharp.Size(mat.Cols, mat.Rows);
 
            Cv2.WarpAffine(mat, warpDst, rot_mat, dst_sz);
 
            pictureBox2.Image = new Bitmap(warpDst.ToMemoryStream());
        }
    }
}

下载

Demo下载

相关推荐
南门听露10 分钟前
无监督跨域目标检测的语义一致性知识转移
人工智能·目标检测·计算机视觉
夏沫の梦11 分钟前
常见LLM大模型概览与详解
人工智能·深度学习·chatgpt·llama
WeeJot嵌入式26 分钟前
线性代数与数据挖掘:人工智能中的核心工具
人工智能·线性代数·数据挖掘
AI小白龙*1 小时前
Windows环境下搭建Qwen开发环境
人工智能·windows·自然语言处理·llm·llama·ai大模型·ollama
cetcht88882 小时前
光伏电站项目-视频监控、微气象及安全警卫系统
运维·人工智能·物联网
惯师科技2 小时前
TDK推出第二代用于汽车安全应用的6轴IMU
人工智能·安全·机器人·汽车·imu
HPC_fac130520678163 小时前
科研深度学习:如何精选GPU以优化服务器性能
服务器·人工智能·深度学习·神经网络·机器学习·数据挖掘·gpu算力
猎嘤一号4 小时前
个人笔记本安装CUDA并配合Pytorch使用NVIDIA GPU训练神经网络的计算以及CPUvsGPU计算时间的测试代码
人工智能·pytorch·神经网络
天润融通4 小时前
天润融通携手挚达科技:AI技术重塑客户服务体验
人工智能
Elastic 中国社区官方博客6 小时前
使用 Elastic AI Assistant for Search 和 Azure OpenAI 实现从 0 到 60 的转变
大数据·人工智能·elasticsearch·microsoft·搜索引擎·ai·azure