Java+opencv+mysql实现人脸辨识源码(人脸采集入库+人脸辨识相似度

　　Java+opencv+mysql实现人脸辨识源码(人脸采集入库+人脸辨识相似度

　　Java+opencv实现人脸辨识

　　写这篇博客，是因为曾经常常使用python+opencv实现人脸处理，后来发觉java也可以实现，于是便学习了下，以下将代码和实现过程贴出。

　　目录1、环境打算

　　使用到的技术：java+opencv+mysql

　　我这儿用的是opencv4.1，这里可以自行下载(其实只须要一个opencv的dll文件置于java安装目录的bin下边既可)

　　2、代码实现

　　核心opencv人脸识别类（识别算法）：

　　package com.dialect.utils;

import org.opencv.core.*;

import org.opencv.imgcodecs.Imgcodecs;

import org.opencv.imgproc.Imgproc;

import org.opencv.objdetect.CascadeClassifier;

import java.util.Arrays;

/**

* 1. 灰度化（减小图片大小）

* 2. 人脸识别

* 3. 人脸切割

* 4. 规一化(人脸直方图)

* 5. 直方图相似度匹配

*

*

* @Description: 比较两张图片人脸的匹配度

* @date 2019/2/1813:47

*/

public class FaceCompare {

// 初始化人脸探测器

static CascadeClassifier faceDetector;

static {

System.loadLibrary(Core.NATIVE_LIBRARY_NAME);

faceDetector = new CascadeClassifier("E:\\eclipseworkspace\\FaceDectcoSys\\src\\haarcascade_frontalface_default.xml");

}

// 灰度化人脸

public static Mat conv_Mat(String img) {

Mat image0 = Imgcodecs.imread(img);

Mat image1 = new Mat();

// 灰度化

Imgproc.cvtColor(image0, image1, Imgproc.COLOR_BGR2GRAY);

// 探测人脸

MatOfRect faceDetections = new MatOfRect();

faceDetector.detectMultiScale(image1, faceDetections);

// rect中人脸图片的范围

for (Rect rect : faceDetections.toArray()) {

Mat face = new Mat(image1, rect);

return face;

}

return null;

}

public static double compare_image(String img_1, String img_2) {

Mat mat_1 = conv_Mat(img_1);

Mat mat_2 = conv_Mat(img_2);

Mat hist_1 = new Mat();

Mat hist_2 = new Mat();

//颜色范围

MatOfFloat ranges = new MatOfFloat(0f, 256f);

//直方图大小， 越大匹配越精确 (越慢)

MatOfInt histSize = new MatOfInt(1000);

Imgproc.calcHist(Arrays.asList(mat_1), new MatOfInt(0), new Mat(), hist_1, histSize, ranges);

Imgproc.calcHist(Arrays.asList(mat_2), new MatOfInt(0), new Mat(), hist_2, histSize, ranges);

// CORREL 相关系数

double res = Imgproc.compareHist(hist_1, hist_2, Imgproc.CV_COMP_CORREL);

return res;

}

public static void main(String[] args) {

String basePicPath = "E:\\eclipseworkspace\\FaceDectcoSys\\WebContent\\static\\images\\";

double compareHist = compare_image(basePicPath + "fbb1.jpg", basePicPath + "fbb2.jpg");

System.out.println(compareHist);

if (compareHist > 0.72) {

System.out.println("人脸匹配");

} else {

System.out.println("人脸不匹配");

}

}

}

　　测试两张图片相似度（美女相片自己网上找）：

　　

　　

　　测试结果：相似度0.82左右，还好了

　　

　　接着实现网页

　　数据库dao：

　　package com.dialect.info.dao;

import java.sql.Connection;

import java.sql.PreparedStatement;

import java.sql.ResultSet;

import java.util.ArrayList;

import java.util.List;

import java.util.UUID;

import com.dialect.info.bean.Dect;

/**

* 人脸信息DAO接口

* @author admin

* @version 2020-05-10

*/

public class DectDao {

/**

* 添加

* @param con

* @param Dialect

* @return

* @throws Exception

*/

public int add(Connection con,Dect dect)throws Exception{

dect.setId(UUID.randomUUID().toString().replace("-", ""));

String sql="insert into dect values(?,?)";

PreparedStatement pstmt=con.prepareStatement(sql);

pstmt.setString(1,dect.getId());

pstmt.setString(2,dect.getBase64());

return pstmt.executeUpdate();

}

/**

* 查询所有

* @param con

* @param dialect

* @return

* @throws Exception

*/

public List list(Connection con)throws Exception{

List list = new ArrayList();

Dect entity=null;

String sql = "select a.* from dect a";

PreparedStatement pstmt=con.prepareStatement(sql);

ResultSet rs=pstmt.executeQuery();

while(rs.next()){

entity = new Dect();

entity.setId(rs.getString("id"));

entity.setBase64(rs.getString("base64"));

list.add(entity);

}

return list;

}

}

　　service层：

　　package com.dialect.info.service.impl;

import java.sql.Connection;

import java.util.List;

import com.dialect.info.bean.Dect;

import com.dialect.info.dao.DectDao;

import com.dialect.info.service.DectService;

import com.dialect.utils.DbUtil;

import com.dialect.utils.Page;

/**

* 人脸信息DAO接口

* @author admin

* @version 2020-05-10

*/

public class DectServiceImpl implements DectService {

DectDao dectDao = new DectDao();

@Override

public int add(Dect dect) {

try {

Connection con = DbUtil.getCon();

Integer result =dectDao.add(con, dect);

DbUtil.closeCon(con);

return result;

} catch (Exception e) {

e.printStackTrace();

}

return 0;

}

@Override

public List select() {

try {

Connection con = DbUtil.getCon();

List list = dectDao.list(con);

DbUtil.closeCon(con);

return list;

} catch (Exception e) {

e.printStackTrace();

}

return null;

}

}

　　control控制层：

　　package com.dialect.info.controller;

import java.io.File;

import java.io.FileOutputStream;

import java.io.IOException;

import java.io.InputStream;

import java.io.PrintWriter;

import java.util.List;

import javax.servlet.ServletException;

import javax.servlet.annotation.WebServlet;

import javax.servlet.http.HttpServlet;

import javax.servlet.http.HttpServletRequest;

import javax.servlet.http.HttpServletResponse;

import org.apache.commons.fileupload.FileItem;

import org.apache.commons.fileupload.disk.DiskFileItemFactory;

import org.apache.commons.fileupload.servlet.ServletFileUpload;

import com.dialect.info.bean.Dect;

import com.dialect.info.dao.DectDao;

import com.dialect.info.service.DectService;

import com.dialect.info.service.impl.DectServiceImpl;

import com.dialect.utils.Page;

import com.dialect.utils.picToBase64;

import com.dialect.utils.FaceCompare;

@WebServlet("/dect")

public class DectController extends HttpServlet {

private static final long serialVersionUID = 1L;

DectDao dectDao=new DectDao();

DectService dectService = new DectServiceImpl();

protected void doGet(HttpServletRequest request, HttpServletResponse response) throws ServletException, IOException {

doPost(request, response);

}

protected void doPost(HttpServletRequest request, HttpServletResponse response) throws ServletException, IOException {

String method = request.getParameter("method");

if ("upload".equals(method)) {

upload(request,response);

}else if ("select".equals(method)) {

select(request, response);

}else if ("list".equals(method)) {

list(request, response);

}else if ("form".equals(method)) {

form(request, response);

}

}

//添加

private void upload(HttpServletRequest request, HttpServletResponse response) throws ServletException, IOException {

System.err.println("---开始上传---");

String para = request.getParameter("base64");

String s = para.replace("data:image/jpeg;base64,","");

System.err.println(para);

System.err.println(s);

Dect dect = new Dect();

dect.setBase64(s);

int res = dectService.add(dect);

// System.err.println(res);

// String res = "1";

// String res2 = "3";

// 解决json中文乱码

response.setContentType("text/json;charset=UTF-8");

response.setCharacterEncoding("UTF-8");

PrintWriter out = response.getWriter();

// String str ="{\"success\":"+res+",\"age\":"+res2 +"}";

String str ="{\"success\":"+res+"}";

out.println(str);

out.flush();

out.close();

}

//添加

private void select(HttpServletRequest request, HttpServletResponse response) throws ServletException, IOException {

System.err.println("---进来了select方法---");

FaceCompare faceCompare = new FaceCompare();

String para = request.getParameter("base64");

String s = para.replace("data:image/jpeg;base64,","");

System.err.println(para);

System.err.println(s);

picToBase64 pic = new picToBase64();

String imgPath1 = "E:\\eclipseworkspace\\FaceDectcoSys\\WebContent\\static\\images\\img1.jpg";

String imgPath2 = "E:\\eclipseworkspace\\FaceDectcoSys\\WebContent\\static\\images\\img2.jpg";

// String imgPath1 = "E:\\img1.jpg";

// String imgPath2 = "E:\\img2.jpg";

//String imgPath2 = "E:\\eclipseworkspace\\FaceDectcogSys\\WebContent\\static\\images\\img2";

pic.Base64ToImage(s, imgPath1);

List list = dectService.select();

int shibie_flag = 0;

double res = 0;

System.err.println(list.size());

if (list.size()>0){

for(Dect dect:list){

System.err.println(dect.getBase64());

String s1 = dect.getBase64().replace("data:image/jpeg;base64,","");

System.err.println("s1:"+s1);

picToBase64 pic2 = new picToBase64();

pic2.Base64ToImage(s1, imgPath2);

res = faceCompare.compare_image(imgPath1, imgPath2);

if (res > 0.72){

System.out.println("人脸匹配");

shibie_flag = 1;

break;

}

}

}

response.setContentType("text/json;charset=UTF-8");

response.setCharacterEncoding("UTF-8");

PrintWriter out = response.getWriter();

String str ="{\"success\":"+shibie_flag+",\"res\":"+res +"}";

// String str ="{\"success\":"+res+"}";

out.println(str);

out.flush();

out.close();

// response.sendRedirect(contextPath+"/dialect?method=list");

}

//列表查询

private void list(HttpServletRequest request, HttpServletResponse response) throws ServletException, IOException {

request.getRequestDispatcher("/dectList2.jsp").forward(request, response);

}

//form跳转页面

private void form(HttpServletRequest request, HttpServletResponse response) throws ServletException, IOException {

request.getRequestDispatcher("/dectList3.jsp").forward(request, response);

}

}

　　3、运行疗效

　　网站操作流程如下：

　　第一步：人脸采集（支持上传图片预览）

　　

　　入库成功：

　　

　　开始人脸辨识（人脸匹配成功）：

　　

　　写在最后：因篇幅有限，不能讲所有代码贴出，如果须要可以加我：3459067873