最近研究C#相关的OCR技术，图像识别一般C和C++这种底层语言做的比较多，C#主要是依托一些封装好的组件进行调用，这里介绍三种身份证识别的方法。
一：调用大公司API接口，百度、云脉，文通科技都有相关的API介绍。
二：调用图像处理类库，EmguCV是OpenCV的一个跨平台的.Net封装，该封装也可以被编译到Mono平台和允许在Windows、Mac OS、Android、iPhone、iPad等多个平台上运行
三：调用Office2007 组件
一、证件识别API接口
以聚合数据中的API接口为例，因为官方API没有提供C#的调用方式，网址如下：证件识别接口
/// <summary>
/// 上传图片
/// </summary>
/// <returns></returns>
public static string CardUpload()
{
try
{
string appkey = "网站自己申请的key"; //配置您申请的appkey
HttpPostedFile file = HttpContext.Current.Request.Files[0];
string url = "http://api2.juheapi.com/cardrecon/upload";
var parameters = new Dictionary<string, string>();
parameters.Add("key", appkey);
parameters.Add("cardType", "2");
string result = HttpPostData(url, 60000, "pic", file.InputStream, parameters);
JObject info = JObject.Parse(JObject.Parse(result)["result"].ToString());
var cardInfo = new
{
name = info["姓名"],
card = info["公民身份号码"]
};
return cardInfo.ToJson();
}
catch (Exception ex)
{
return ex.ToString();
}
}
/// <summary>
/// Post调用API
/// </summary>
/// <param name="url">api地址</param>
/// <param name="timeOut">访问超时时间</param>
/// <param name="fileKeyName">文件参数名</param>
/// <param name="file">文件流</param>
/// <param name="stringDict">参数列表</param>
/// <returns>结果集</returns>
private static string HttpPostData(string url, int timeOut, string fileKeyName,
Stream file, Dictionary<string, string> stringDict)
{
string responseContent;
var memStream = new MemoryStream();
var webRequest = (HttpWebRequest)WebRequest.Create(url);
// 边界符
var boundary = "---------------" + DateTime.Now.Ticks.ToString("x");
// 边界符
var beginBoundary = Encoding.ASCII.GetBytes("--" + boundary + "
");
// 最后的结束符
var endBoundary = Encoding.ASCII.GetBytes("--" + boundary + "--
");
// 设置属性
webRequest.Method = "POST";
webRequest.Timeout = timeOut;
webRequest.ContentType = "multipart/form-data; boundary=" + boundary;
//写入开始边界符
memStream.Write(beginBoundary, 0, beginBoundary.Length);
// 写入文件
const string filePartHeader =
"Content-Disposition: form-data; name="{0}"; filename="{1}"
" +
"Content-Type: application/octet-stream
";
var header = string.Format(filePartHeader, fileKeyName, "card.jpg");
var headerbytes = Encoding.UTF8.GetBytes(header);
memStream.Write(headerbytes, 0, headerbytes.Length);
file.CopyTo(memStream);
// 写入字符串的Key
var stringKeyHeader = "
--" + boundary +
"
Content-Disposition: form-data; name="{0}"" +
"
{1}
";
foreach (byte[] formitembytes in from string key in stringDict.Keys
select string.Format(stringKeyHeader, key, stringDict[key])
into formitem
select Encoding.UTF8.GetBytes(formitem))
{
memStream.Write(formitembytes, 0, formitembytes.Length);
}
// 写入最后的结束边界符
memStream.Write(endBoundary, 0, endBoundary.Length);
webRequest.ContentLength = memStream.Length;
// 构造完毕，执行POST方法
var requestStream = webRequest.GetRequestStream();
memStream.Position = 0;
var tempBuffer = new byte[memStream.Length];
memStream.Read(tempBuffer, 0, tempBuffer.Length);
memStream.Close();
requestStream.Write(tempBuffer, 0, tempBuffer.Length);
requestStream.Close();
var httpWebResponse = (HttpWebResponse)webRequest.GetResponse();
using (var httpStreamReader = new StreamReader(httpWebResponse.GetResponseStream(),
Encoding.GetEncoding("utf-8")))
{
responseContent = httpStreamReader.ReadToEnd();
}
httpWebResponse.Close();
webRequest.Abort();
return responseContent;
}二、EmguCV类库调用
环境搭建
下载地址：EmguCV官网
在File类别下下载这个EXE，进行安装，安装后在目录下能找相应组件，还有些应用的案例。
C#进行识别，需进行图片二值化处理和OCR调用相关DLL可在我整理的地址下载：360云盘 提取码：89f4
dll文件夹中的dll引用到C#项目中，x64，x86，tessdata对应OCR识别的类库和语言库，我tessdata中已添加中文语言包，将这三个文件夹放入程序执行文件夹中。
Demo
自己做的小Demo如图：身份证图片是百度上下载的
相关代码如下：
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 Emgu.CV;
using Emgu.CV.OCR;
using Emgu.CV.Structure;
using System.IO;
namespace ImageManage
{
public partial class Form1 : Form
{
Image<Gray, Byte> imageThreshold;
public Form1()
{
InitializeComponent();
}
private void btn_convert_Click(object sender, EventArgs e)
{
//第一个参数是语言包文件夹的地址，不写默认在执行文件夹下
Tesseract _ocr = new Tesseract("", "chi_sim", OcrEngineMode.TesseractOnly);
_ocr.Recognize(imageThreshold);
String text = _ocr.GetText();
this.textBox1.Text = text;
}
private void pictureBox1_Click(object sender, EventArgs e)
{
OpenFileDialog of = new OpenFileDialog();
of.Title = "请选择图片";
if (of.ShowDialog() == DialogResult.OK)
{
string file = of.FileName;
Image img = Image.FromFile(file);
pictureBox1.Image = img;
}
Bitmap bitmap = (Bitmap)this.pictureBox1.Image;
Image<Bgr, Byte> imageSource = new Image<Bgr, byte>(bitmap);
Image<Gray, Byte> imageGrayscale = imageSource.Convert<Gray, Byte>();
imageGrayscale = randon(imageGrayscale);
imageThreshold = imageGrayscale.ThresholdBinary(new Gray(100), new Gray(255));
this.pictureBox2.Image = imageThreshold.ToBitmap();
}
/// <summary>
/// 旋转校正
/// </summary>
/// <param name="imageInput"></param>
/// <returns></returns>
private Image<Gray, Byte> randon(Image<Gray, Byte> imageInput)//图像投影旋转法倾斜校正子函数定义
{
int nwidth = imageInput.Width;
int nheight = imageInput.Height;
int sum;
int SumOfCha;
int SumOfChatemp = 0;
int[] sumhang = new int[nheight];
Image<Gray, Byte> resultImage = imageInput;
Image<Gray, Byte> ImrotaImage;
//20度范围内的调整
for (int ang = -20; ang < 20; ang = ang + 1)
{
ImrotaImage = imageInput.Rotate(ang, new Gray(1));
for (int i = 0; i < nheight; i++)
{
sum = 0;
for (int j = 0; j < nwidth; j++)
{
sum += ImrotaImage.Data[i, j, 0];
}
sumhang[i] = sum;
}
SumOfCha = 0;
for (int k = 0; k < nheight - 1; k++)
{
SumOfCha = SumOfCha + (Math.Abs(sumhang[k] - sumhang[k + 1]));
}
if (SumOfCha > SumOfChatemp)
{
resultImage = ImrotaImage;
SumOfChatemp = SumOfCha;
}
}
return resultImage;
}
}
}三、Office 2007组件
该组件免费而且识别度比较高。
环境搭建
Office 2007组件MODI，需要安装Ofiice2007，且由于兼容性需要安装补丁，SP1或者SP2都行，补丁下载地址如下：
SP1下载地址 SP2下载地址
安装后控制面板-->卸载或更新程序-->选择Office2007-->选择更改-->选择添加或修复功能-->弹出下面界面，运行相应组件。
将Office工具-->Microsoft Office Document Imaging 下的工具运行
在C#项目中引用Com组件即可：
如果Office组件应用不是在本地程序而需要部署在IIS上，还需将应用程序的应用池的权限设置为如下图所示：程序应用池-->高级设置-->标识
Demo
StringBuilder sb = new StringBuilder();
MODI.Document doc = new MODI.Document();
doc.Create(fullFileName);
MODI.Image image;
MODI.Layout layout;
doc.OCR(MODI.MiLANGUAGES.miLANG_CHINESE_SIMPLIFIED, true, true); // 识别文字类型
for (int i = 0; i < doc.Images.Count; i++)
{
image = (MODI.Image)doc.Images[i];
layout = image.Layout;
sb.Append(layout.Text);
}以上即一些C#进行身份证识别的方法，可根据自己项目的不同需求进行选用。