前言
OpenCV的 全称是:Open Source Computer Vision Library。OpenCV是一个基于BSD许可(开源)发行的跨平台计算机视觉库,可以运行在Linux、Windows、Android和Mac OS操作系统上。它轻量级而且高效——由一系列 C 函数和少量 C++ 类 构成,同时提供了Python、Ruby、MATLAB等语言的接口,实现了 图像处理和计算机视觉方面的很多通用算法。
OpenCV用C++语言编写,它的主要接口也是C++语言,但是依然保留了大量的C语言接口。该库也有大量的Python, Java and MATLAB/OCTAVE (版本2.5)的接口。这些语言的API接口函数可以通过在线文档获得。如今也提供对于C#,Ch, Ruby的支持。
本文着重讲述opencv+java的实现程序,关于opencv的如何引入dll库等操作以及c的实现就不在这里概述了
方法如下
直接开始,首先下载opencv,引入opencv-246.jar包以及对应dll库
1.背景去除 简单案列,只适合背景单一的图像
import java.util.ArrayList;
import java.util.List;
import org.opencv.core.Core;
import org.opencv.core.CvType;
import org.opencv.core.Mat;
import org.opencv.core.Point;
import org.opencv.core.Scalar;
import org.opencv.core.Size;
import org.opencv.highgui.Highgui;
import org.opencv.imgproc.Imgproc;
public class demo1 {
public static void main(String[] args) {
System.loadLibrary("opencv_java246");
Mat img = Highgui.imread("E:\\opencv_img\\source\\1.jpg");//读图像
Mat new_img = doBackgroundRemoval(img);
Highgui.imwrite("E:\\opencv_img\\target\\1.jpg",new_img);//写图像
}
private static Mat doBackgroundRemoval(Mat frame) {
// init
Mat hsvImg = new Mat();
List<Mat> hsvPlanes = new ArrayList<>();
Mat thresholdImg = new Mat();
int thresh_type = Imgproc.THRESH_BINARY_INV;
// threshold the image with the average hue value
hsvImg.create(frame.size(), CvType.CV_8U);
Imgproc.cvtColor(frame, hsvImg, Imgproc.COLOR_BGR2HSV);
Core.split(hsvImg, hsvPlanes);
// get the average hue value of the image
Scalar average = Core.mean(hsvPlanes.get(0));
double threshValue = average.val[0];
Imgproc.threshold(hsvPlanes.get(0), thresholdImg, threshValue, 179.0,
thresh_type);
Imgproc.blur(thresholdImg, thresholdImg, new Size(5, 5));
// dilate to fill gaps, erode to smooth edges
Imgproc.dilate(thresholdImg, thresholdImg, new Mat(),
new Point(-1, -1), 1);
Imgproc.erode(thresholdImg, thresholdImg, new Mat(), new Point(-1, -1),
3);
Imgproc.threshold(thresholdImg, thresholdImg, threshValue, 179.0,
Imgproc.THRESH_BINARY);
// create the new image
Mat foreground = new Mat(frame.size(), CvType.CV_8UC3, new Scalar(255,
255, 255));
thresholdImg.convertTo(thresholdImg, CvType.CV_8U);
frame.copyTo(foreground, thresholdImg);// 掩膜图像复制
return foreground;
}
}
2.边缘检测
import org.opencv.core.Core;
import org.opencv.core.Mat;
import org.opencv.core.Size;
import org.opencv.highgui.Highgui;
import org.opencv.imgproc.Imgproc;
public class demo2 {
public static void main(String[] args) {
System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
Mat img = Highgui.imread("E:\\face7.jpg");//读图像
Mat new_img = doCanny(img);
Highgui.imwrite("E:\\opencv_img\\target\\2.jpg",new_img);//写图像
}
private static Mat doCanny(Mat frame)
{
// init
Mat grayImage = new Mat();
Mat detectedEdges = new Mat();
double threshold = 10;
// convert to grayscale
Imgproc.cvtColor(frame, grayImage, Imgproc.COLOR_BGR2GRAY);
// reduce noise with a 3x3 kernel
Imgproc.blur(grayImage, detectedEdges, new Size(3, 3));
// canny detector, with ratio of lower:upper threshold of 3:1
Imgproc.Canny(detectedEdges, detectedEdges, threshold, threshold * 3);
// using Canny's output as a mask, display the result
Mat dest = new Mat();
frame.copyTo(dest, detectedEdges);
return dest;
}
}
3.人脸检测技术 (靠边缘的和侧脸检测不准确)
import org.opencv.core.Core;
import org.opencv.core.Mat;
import org.opencv.core.MatOfRect;
import org.opencv.core.Point;
import org.opencv.core.Rect;
import org.opencv.core.Scalar;
import org.opencv.highgui.Highgui;
import org.opencv.objdetect.CascadeClassifier;
public class demo3 {
public static void main(String[] args) {
System.out.println("Hello, OpenCV");
// Load the native library.
System.loadLibrary("opencv_java246");
new demo3().run();
}
public void run() {
System.out.println("\nRunning DetectFaceDemo");
System.out.println(getClass().getResource("/haarcascade_frontalface_alt2.xml").getPath());
// Create a face detector from the cascade file in the resources
// directory.
//CascadeClassifier faceDetector = new CascadeClassifier(getClass().getResource("haarcascade_frontalface_alt2.xml").getPath());
//Mat image = Highgui.imread(getClass().getResource("lena.png").getPath());
//注意:源程序的路径会多打印一个‘/',因此总是出现如下错误
//因此,我们将第一个字符去掉
String xmlfilePath=getClass().getResource("/haarcascade_frontalface_alt2.xml").getPath().substring(1);
CascadeClassifier faceDetector = new CascadeClassifier(xmlfilePath);
Mat image = Highgui.imread("E:\\face2.jpg");
// Detect faces in the image.
// MatOfRect is a special container class for Rect.
MatOfRect faceDetections = new MatOfRect();
faceDetector.detectMultiScale(image, faceDetections);
System.out.println(String.format("Detected %s faces", faceDetections.toArray().length));
// Draw a bounding box around each face.
for (Rect rect : faceDetections.toArray()) {
Core.rectangle(image, new Point(rect.x, rect.y), new Point(rect.x + rect.width, rect.y + rect.height), new Scalar(0, 255, 0));
}
// Save the visualized detection.
String filename = "E:\\faceDetection.png";
System.out.println(String.format("Writing %s", filename));
System.out.println(filename);
Highgui.imwrite(filename, image);
}
}
人脸检测需要自行下载haarcascade_frontalface_alt2.xml文件
附上demo下载地址:点击这里,运行需自行引入opencv的dll文件
总结
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