1、创建Java工程，并导入如下jar包

opencv-440.jar

2、编写代码

import org.opencv.core.*;

import org.opencv.imgcodecs.Imgcodecs;

import org.opencv.imgproc.Imgproc;

import org.opencv.objdetect.CascadeClassifier;

import java.util.Arrays;

/**

* 人类匹配

*/

public class FaceCompare {

// 初始化人脸探测器

static CascadeClassifier faceDetector;

static {

//路径不能包含中文 linux使用libopencv_java410.so

String opencvDllName = "D:\\java_project\\opencv440-testFace\\lib\\opencv440\\build\\java\\x64\\opencv_java440.dll";

System.load(opencvDllName);

// xml路径不能包含中文

String property = System.getProperty("user.dir") + "\\lib\\opencv440\\build\\etc\\haarcascades\\";

faceDetector = new CascadeClassifier(property + "haarcascade_frontalface_alt.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(10000000);

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) {

//图片路径不能包含中文

String str1 = "D:\\Documents\\Pictures\\2020-07-28_03+55+49_.png";

String str2 = "D:\\Documents\\Pictures\\2020-07-28_03+55+53_.png";

double compareHist = compare_image(str1, str2);

System.out.println(compareHist);

if (compareHist > 0.72) {

System.out.println("人脸匹配");

} else {

System.out.println("人脸不匹配");

}

}

}