基于C#技术实现身份证识别功能

最近研究c#相关的orc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 + "\r\n");
// 最后的结束符
var endboundary = encoding.ascii.getbytes("--" + boundary + "--\r\n");
// 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}\"\r\n" +
"content-type: application/octet-stream\r\n\r\n";
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 = "\r\n--" + boundary +
"\r\ncontent-disposition: form-data; name=\"{0}\"" +
"\r\n\r\n{1}\r\n";
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。