Java使用OpenCV实现人脸识别/人眼检测/图片截取/合成/添加水印

官方下载opencv安装文件: http://opencv.org/releases.html，以windows版本为例，下载opencv-3.1.0.exe
安装后，在build目录下 D:\opencv\opencv\build\java，获取opencv-310.jar，copy至项目opncv目录（需要新建）

同时需要dll文件 与 各识别xml文件，进行不同特征的识别（人脸，侧脸，眼睛等）

dll目录： D:\opencv\opencv\build\java\x64\opencv_java2413.dll （dll库）

xml目录：D:\opencv\opencv\sources\data\haarcascades\haarcascade_frontalface_alt.xml（目录中有各类识别文件）

下面给出图片的各种操作的源码和运行结果，源码中有各个操作的解释，看代码就可以理解，java代码如下

package com.zmx.opencvtest;

import org.opencv.core.*;
import org.opencv.core.Point;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;
import org.opencv.objdetect.CascadeClassifier;

import javax.imageio.ImageIO;
import javax.swing.*;
import java.awt.*;
import java.awt.image.BufferedImage;
import java.io.File;
import java.io.IOException;

/**
* Created by Administrator on 2017/8/17.
*/
public class DetectFaceTest {

static{
// 载入opencv的库
String opencvpath = System.getProperty("user.dir") + "\\opencv\\x64\\";
String opencvDllName = opencvpath + Core.NATIVE_LIBRARY_NAME + ".dll";
System.load(opencvDllName);
}

/**
* opencv实现人脸识别
* @param imagePath
* @param outFile
* @throws Exception
*/
public static void detectFace(String imagePath, String outFile) throws Exception
{

System.out.println("Running DetectFace ... ");
// 从配置文件lbpcascade_frontalface.xml中创建一个人脸识别器，该文件位于opencv安装目录中
CascadeClassifier faceDetector = new CascadeClassifier(
"D:\\opencv\\opencv\\sources\\data\\haarcascades\\haarcascade_frontalface_alt.xml");

Mat image = Imgcodecs.imread(imagePath);

// 在图片中检测人脸
MatOfRect faceDetections = new MatOfRect();

faceDetector.detectMultiScale(image, faceDetections);

System.out.println(String.format("Detected %s faces", faceDetections.toArray().length));

Rect[] rects = faceDetections.toArray();
if(rects != null && rects.length > 1){
throw new RuntimeException("超过一个脸");
}
// 在每一个识别出来的人脸周围画出一个方框
Rect rect = rects[0];

Imgproc.rectangle(image, new Point(rect.x-2, rect.y-2),
new Point(rect.x + rect.width, rect.y + rect.height),
new Scalar(0, 255, 0));

Imgcodecs.imwrite(outFile, image);
System.out.println(String.format("人脸识别成功，人脸图片文件为： %s", outFile));

}

/**
* opencv实现人眼识别
* @param imagePath
* @param outFile
* @throws Exception
*/
public static void detectEye(String imagePath, String outFile) throws Exception {

CascadeClassifier eyeDetector = new CascadeClassifier(
"D:\\opencv\\opencv\\sources\\data\\haarcascades\\haarcascade_eye.xml");

Mat image = Imgcodecs.imread(imagePath); //读取图片

// 在图片中检测人脸
MatOfRect faceDetections = new MatOfRect();

eyeDetector.detectMultiScale(image, faceDetections, 2.0,1,1,new Size(20,20),new Size(20,20));

System.out.println(String.format("Detected %s eyes", faceDetections.toArray().length));
Rect[] rects = faceDetections.toArray();
if(rects != null && rects.length <2){
throw new RuntimeException("不是一双眼睛");
}
Rect eyea = rects[0];
Rect eyeb = rects[1];

System.out.println("a-中心坐标 " + eyea.x + " and " + eyea.y);
System.out.println("b-中心坐标 " + eyeb.x + " and " + eyeb.y);

//获取两个人眼的角度
double dy=(eyeb.y-eyea.y);
double dx=(eyeb.x-eyea.x);
double len=Math.sqrt(dx*dx+dy*dy);
System.out.println("dx is "+dx);
System.out.println("dy is "+dy);
System.out.println("len is "+len);

double angle=Math.atan2(Math.abs(dy),Math.abs(dx))*180.0/Math.PI;
System.out.println("angle is "+angle);

for(Rect rect:faceDetections.toArray()) {
Imgproc.rectangle(image, new Point(rect.x, rect.y), new Point(rect.x
+ rect.width, rect.y + rect.height), new Scalar(0, 255, 0));
}
Imgcodecs.imwrite(outFile, image);

System.out.println(String.format("人眼识别成功，人眼图片文件为： %s", outFile));

}

/**
* 裁剪图片并重新装换大小
* @param imagePath
* @param posX
* @param posY
* @param width
* @param height
* @param outFile
*/
public static void imageCut(String imagePath,String outFile, int posX,int posY,int width,int height ){

//原始图像
Mat image = Imgcodecs.imread(imagePath);

//截取的区域：参数,坐标X,坐标Y,截图宽度,截图长度
Rect rect = new Rect(posX,posY,width,height);

//两句效果一样
Mat sub = image.submat(rect); //Mat sub = new Mat(image,rect);

Mat mat = new Mat();
Size size = new Size(300, 300);
Imgproc.resize(sub, mat, size);//将人脸进行截图并保存

Imgcodecs.imwrite(outFile, mat);
System.out.println(String.format("图片裁切成功，裁切后图片文件为： %s", outFile));

}

/**
*
* @param imagePath
* @param outFile
*/
public static void setAlpha(String imagePath, String outFile) {
/**
* 增加测试项
* 读取图片，绘制成半透明
*/
try {

ImageIcon imageIcon = new ImageIcon(imagePath);

BufferedImage bufferedImage = new BufferedImage(imageIcon.getIconWidth(),
imageIcon.getIconHeight(), BufferedImage.TYPE_4BYTE_ABGR);

Graphics2D g2D = (Graphics2D) bufferedImage.getGraphics();

g2D.drawImage(imageIcon.getImage(), 0, 0, imageIcon.getImageObserver());

//循环每一个像素点，改变像素点的Alpha值
int alpha = 100;
for (int j1 = bufferedImage.getMinY(); j1 < bufferedImage.getHeight(); j1++) {
for (int j2 = bufferedImage.getMinX(); j2 < bufferedImage.getWidth(); j2++) {
int rgb = bufferedImage.getRGB(j2, j1);
rgb = ( (alpha + 1) << 24) | (rgb & 0x00ffffff);
bufferedImage.setRGB(j2, j1, rgb);
}
}
g2D.drawImage(bufferedImage, 0, 0, imageIcon.getImageObserver());

//生成图片为PNG
ImageIO.write(bufferedImage, "png", new File(outFile));

System.out.println(String.format("绘制图片半透明成功，图片文件为： %s", outFile));

}
catch (Exception e) {
e.printStackTrace();
}

}

/**
* 为图像添加水印
* @param buffImgFile 底图
* @param waterImgFile 水印
* @param outFile 输出图片
* @param alpha 透明度
* @throws IOException
*/
private static void watermark(String buffImgFile,String waterImgFile,String outFile, float alpha) throws IOException {
// 获取底图
BufferedImage buffImg = ImageIO.read(new File(buffImgFile));

// 获取层图
BufferedImage waterImg = ImageIO.read(new File(waterImgFile));

// 创建Graphics2D对象，用在底图对象上绘图
Graphics2D g2d = buffImg.createGraphics();

int waterImgWidth = waterImg.getWidth();// 获取水印层图的宽度

int waterImgHeight = waterImg.getHeight();// 获取水印层图的高度

// 在图形和图像中实现混合和透明效果
g2d.setComposite(AlphaComposite.getInstance(AlphaComposite.SRC_ATOP, alpha));

// 绘制
g2d.drawImage(waterImg, 0, 0, waterImgWidth, waterImgHeight, null);

g2d.dispose();// 释放图形上下文使用的系统资源

//生成图片为PNG
ImageIO.write(buffImg, "png", new File(outFile));

System.out.println(String.format("图片添加水印成功，图片文件为： %s", outFile));
}

/**
* 图片合成
* @param image1
* @param image2
* @param posw
* @param posh
* @param outFile
* @return
*/
public static void simpleMerge(String image1, String image2, int posw, int posh, String outFile) throws IOException{

// 获取底图
BufferedImage buffImg1 = ImageIO.read(new File(image1));

// 获取层图
BufferedImage buffImg2 = ImageIO.read(new File(image2));

//合并两个图像
int w1 = buffImg1.getWidth();
int h1 = buffImg1.getHeight();

int w2 = buffImg2.getWidth();
int h2 = buffImg2.getHeight();

BufferedImage imageSaved = new BufferedImage(w1, h1, BufferedImage.TYPE_INT_ARGB); //创建一个新的内存图像

Graphics2D g2d = imageSaved.createGraphics();

g2d.drawImage(buffImg1, null, 0, 0); //绘制背景图像

for (int i = 0; i < w2; i++) {
for (int j = 0; j < h2; j++) {
int rgb1 = buffImg1.getRGB(i + posw, j + posh);
int rgb2 = buffImg2.getRGB(i, j);

/*if (rgb1 != rgb2) {
rgb2 = rgb1 & rgb2;
}*/
imageSaved.setRGB(i + posw, j + posh, rgb2); //修改像素值
}
}

ImageIO.write(imageSaved, "png", new File(outFile));

System.out.println(String.format("图片合成成功，合成图片文件为： %s", outFile));

}

public static void main(String[] args) throws Exception {

//人脸识别
detectFace("E:\\person.jpg", "E:\\personFaceDetect.png");

//人眼识别
detectEye("E:\\person.jpg", "E:\\personEyeDetect.png");

//图片裁切
imageCut("E:\\person.jpg","E:\\personCut.png", 50, 50,100,100);

//设置图片为半透明
setAlpha("E:\\person.jpg", "E:\\personAlpha.png");

//为图片添加水印
watermark("E:\\person.jpg","E:\\ling.jpg","E:\\personWaterMark.png", 0.2f);

//图片合成
simpleMerge("E:\\person.jpg", "E:\\ling.jpg", 45, 50, "E:\\personMerge.png");

}
}



     上述运行的结果如下：
（1）原图： E:\person.jpg     水印的图片：E:\ling.jpg


      


Running DetectFace ... 

Detected 1 faces

（2）人脸识别成功，人脸图片文件为： E:\personFaceDetect.png



（3）Detected 4 eyes

a-中心坐标 93 and 102

b-中心坐标 59 and 107

dx is -34.0

dy is 5.0

len is 34.36568055487916

angle is 8.36588612403259

人眼识别成功，人眼图片文件为： E:\personEyeDetect.png



图片裁切成功，裁切后图片文件为： E:\personCut.png



绘制图片半透明成功，图片文件为： E:\personAlpha.png



图片添加水印成功，图片文件为： E:\personWaterMark.png



图片合成成功，合成图片文件为： E:\personMerge.png



总结一下，opencv检测眼睛的还是有一些瑕疵，但是人脸检测效果还可以，我的测试就是如此，大家可以参考实现自己的代码。