Java+OpenCV实现人脸检测并自动拍照

java+opencv实现人脸检测，调用笔记本摄像头实时抓拍，人脸会用红色边框标识出来，并且将抓拍的目录存放在src下，图片名称是时间戳。

环境配置：win7 64位，jdk1.8

CameraBasic.java

package com.njupt.zhb.test;

import java.awt.EventQueue;

import javax.swing.ImageIcon;
import javax.swing.JFrame;
import javax.swing.JLabel;

import org.opencv.core.*;
import org.opencv.highgui.Highgui;
import org.opencv.highgui.VideoCapture;
import org.opencv.imgproc.Imgproc;
import org.opencv.objdetect.CascadeClassifier;
/**
 * 动态人脸检测并裁剪
 * @author hyj
 *
 */
public class CameraBasic {
  static {
   System.out.println(System.getProperty("java.library.path"));
    System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
  }
  private JFrame frame;
  private static JLabel label;
  private static int flag = 0;

  public static void main(String[] args) {
    EventQueue.invokeLater(new Runnable() {
      @Override
      public void run() {
        try {
          CameraBasic window = new CameraBasic();
          window.frame.setVisible(true);
        } catch (Exception e) {
          e.printStackTrace();
        }
      }
    });

    VideoCapture camera = new VideoCapture();//创建Opencv中的视频捕捉对象
    camera.open(0);//open函数中的0代表当前计算机中索引为0的摄像头，如果你的计算机有多个摄像头，那么一次1,2,3……
    if (!camera.isOpened()) {//isOpened函数用来判断摄像头调用是否成功
      System.out.println("Camera Error");//如果摄像头调用失败，输出错误信息
    } else {
      Mat frame = new Mat();//创建一个输出帧
      while (flag == 0) {
        camera.read(frame);//read方法读取摄像头的当前帧
//        CascadeClassifier faceDetector = new CascadeClassifier("src/com/njupt/zhb/test/lbpcascade_frontalface.xml");
        CascadeClassifier faceDetector = new CascadeClassifier("src/com/njupt/zhb/test/haarcascade_frontalface_alt.xml");
        MatOfRect faceDetections = new MatOfRect();
        faceDetector.detectMultiScale(frame, faceDetections);
        Rect [] rectArray = faceDetections.toArray();
        if (rectArray.length > 0) {

          for (int i=0;i<rectArray.length;i++) {
           Rect rect = rectArray[i];
            Rect rectCrop = new Rect(rect.x, rect.y, rect.width, rect.height);
            if (rect.width + rect.height > rectCrop.height + rectCrop.width) {
              rectCrop = new Rect(rect.x, rect.y, rect.width, rect.height);
            }
             System.out.println(String.format("检测到 %s 个人脸！ ", rectArray.length));
             Mat imageRoi = new Mat(frame, rectCrop);
             String name = System.currentTimeMillis()+".png";
             Highgui.imwrite(name, imageRoi);

            Core.rectangle(frame, new Point(rect.x, rect.y), new Point(rect.x + rect.width, rect.y + rect.height), new Scalar(0, 0, 255), 2);
          }
        }

        //转换图像格式并输出
        label.setIcon(new ImageIcon(mat2BufferedImage.matToBufferedImage(frame)));

        try {
          Thread.sleep(500);//线程暂停500ms
        } catch (InterruptedException e) {
          // TODO Auto-generated catch block
          e.printStackTrace();
        }

//        if (faceCount > 0) {
//          faceSerialCount++;
//          System.out.println(faceSerialCount);
//        } else {
//          faceSerialCount = 0;
//        }
//
//        if (faceSerialCount > 6) {
//          Mat imageRoi = new Mat(frame, rectCrop);
//          Highgui.imwrite("haha.png", imageRoi);
//          faceSerialCount = 0;
//        }
      }
    }
  }

  private CameraBasic() {
    initialize();
  }

  private void initialize() {
    frame = new JFrame();
    frame.setBounds(100, 100, 1000, 600);
    frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
    frame.getContentPane().setLayout(null);
    label = new JLabel("");
    label.setBounds(0, 0, 1000, 500);
    frame.getContentPane().add(label);
  }

}

完整源码下载地址：Java+OpenCV实现人脸检测并拍照

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