基于opencv+java实现简单图形识别程序

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;
	}
}

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;
	}
}

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);  
  }  
  
}