opencvjava⼩应⽤：⽐较两个图⽚的相似度
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import *;
入党要求兽人正太import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;
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import org.opencv.objdetect.CascadeClassifier;
import java.util.Arrays;
public class FaceCompareMain {
//初始化⼈脸探测器
static CascadeClassifier faceDetector;
static {
System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
faceDetector = new CascadeClassifier(
"D:\\ib\\face-detact\\src\\com\\company\\haarcascade_l");
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// 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
public static void main(String[] args) {
String baPicPath = "D:\\ib\\face-detact\\src\\pics\\";
double compareHist = compare_image(baPicPath + "11_1.png", baPicPath + "11_2.png");
System.out.println(compareHist);
if (compareHist > 0.72) {
System.out.println("⼈脸匹配");
} el {
System.out.println("⼈脸不匹配");
}
}
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);卡门涡街
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 = pareHist(hist_1, hist_2, Imgproc.CV_COMP_CORREL);
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return res;
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}
// "D:\\ib\\face-detact\\src\\com\\company\\a1.jpg"
private static Mat conv_Mat(String img_1) {
Mat image0 = Imgcodecs.imread(img_1);
Mat image = new Mat();
//灰度转换
Imgproc.cvtColor(image0, image, Imgproc.COLOR_BGR2GRAY);
MatOfRect faceDetections = new MatOfRect();
//探测⼈脸
faceDetector.detectMultiScale(image, faceDetections);
// rect中是⼈脸图⽚的范围
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for (Rect rect : Array()) {
//切割rect⼈脸
Mat mat = new Mat(image, rect);
return mat;
}
return null;
}
}
本⽂使⽤opencv 3.4.5版本，opencv⼤版本api变动不少java项⽬设置，需要引⼊opencv native动态连接库
参考：
