利用OpenCV进行人脸识别

package com.tcl.uviewer.features.featuresImpl;

import org.opencv.core.Core;

import org.opencv.core.Mat;

import org.opencv.core.MatOfRect;

import org.opencv.core.Point;

import org.opencv.core.Scalar;

import org.opencv.highgui.Highgui;

import org.opencv.objdetect.CascadeClassifier;

public class Test

{

public static void detectFace(String p_w_picpathPath)

{

System.out.println(“\nRunning DetectFaceDemo”);

// 导入opencv的库

System.loadLibrary(Core.NATIVE_LIBRARY_NAME);

// 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(

“C:/lbpcascade_frontalface.xml”);

Mat p_w_picpath = Highgui.imread(p_w_picpathPath);

// 在图片中检测人脸

MatOfRect faceDetections = new MatOfRect();

faceDetector.detectMultiScale(p_w_picpath, faceDetections);

System.out.println(String.format(“Detected %s faces”,

faceDetections.toArray().length));

// 在每一个识别出来的人脸周围画出一个方框

for (org.opencv.core.Rect rect : faceDetections.toArray())

{

Core.rectangle(p_w_picpath, new Point(rect.x, rect.y), new Point(rect.x

+ rect.width, rect.y + rect.height), new Scalar(0, 255, 0));

}

// 将结果保存到文件

String filename = “faceDetection.png”;

System.out.println(String.format(“Writing %s”, filename));

Highgui.imwrite(filename, p_w_picpath);

}

public static void main(String[] args)

{

String p_w_picpathPath = “C:/005.jpg”;

Test.detectFace(p_w_picpathPath);

}

}

Running DetectFaceDemo

Detected 33 faces

Writing faceDetection.png