1.环境搭建
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整个项目的结构图
2.编写DetectFaceDemo.java,代码如下：
[java] view plaincopy
package com.njupt.zhb.test;
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;
//
// Detects faces in an image, draws boxes around them, and writes the results
// to "faceDetection.png".
//
public class DetectFaceDemo {
public void run() {
System.out.println("\nRunning DetectFaceDemo");
System.out.println(getClass().getResource("lbpcascade_frontalface.xml").getPath());
// Create a face detector from the cascade file in the resources
// directory.
//CascadeClassifier faceDetector = new CascadeClassifier(getClass().getResource("lbpcascade_frontalface.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
/*
* Detected 0 faces Writing faceDetection.png libpng warning: Image
* width is zero in IHDR libpng warning: Image height is zero in IHDR
* libpng error: Invalid IHDR data
*/
//因此，我们将第一个字符去掉
String xmlfilePath=getClass().getResource("lbpcascade_frontalface.xml").getPath().substring(1);
CascadeClassifier faceDetector = new CascadeClassifier(xmlfilePath);
Mat image = Highgui.imread(getClass().getResource("we.jpg").getPath().substring(1));
// 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 = "faceDetection.png";
System.out.println(String.format("Writing %s", filename));
Highgui.imwrite(filename, image);
}
}
3.编写测试类：
[java] view plaincopy
package com.njupt.zhb.test;
public class TestMain {
public static void main(String[] args) {
System.out.println("Hello, OpenCV");
// Load the native library.
System.loadLibrary("opencv_java246");
new DetectFaceDemo().run();
}
}
//运行结果:
//Hello, OpenCV
//
//Running DetectFaceDemo
///E:/eclipse_Jee/workspace/JavaOpenCV246/bin/com/njupt/zhb/test/lbpcascade_frontalface.xml
//Detected 8 faces
//Writing faceDetection.png
摘要图像识别是目前很热门的研究领域，涉及的知识很广，包括信息论、模式识别、模糊数学、图像编码、内容分类等等。本文仅对使用Java实现了一个简单的图像文本二值处理，关于识别并未实现。
步骤
建立文本字符模板二值矩阵
对测试字符进行二值矩阵化处理
代码
/*
* @(#)StdModelRepository.java
*
* This program is free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation; either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU Library General Public License for more details.
* You should have received a copy of the GNU General Public License
* along with this program; if not, write to the Free Software
* Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
*/
package cn.edu.ynu.sei.recognition.util;import java.awt.Image;import java.awt.image.BufferedImage;import java.io.File;import java.io.IOException;import java.util.ArrayList;import java.util.List;import java.util.logging.Level;import java.util.logging.Logger;import javax.imageio.ImageIO;/** * Hold character charImgs as standard model repository.
* @author 88250
* @version 1.0.0.0, Mar 20, 2008
*/
public class StdModelRepository {
/** * hold character images
*/ List charImgs = new ArrayList();
/** * default width of a character
*/ static int width = 16 /** * default height of a character
*/ static int height = 28 /** * standard character model matrix
*/ public int[][][] stdCharMatrix = new int[27][width][height];
/** * Default constructor.
*/ public StdModelRepository() {
BufferedImage lowercase = null try {
lowercase = ImageIO.read(new File("lowercase.png"));
} catch (IOException ex) {
Logger.getLogger(StdModelRepository.class.getName()).
log(Level.SEVERE, null, ex);
}
for (int i = 0 i 26 i++) {
charImgs.add(lowercase.getSubimage(i * width,
0,
width,
height));
}
for (int i = 0 i charImgs.size(); i++) {
Image image = charImgs.get(i);
int[] pixels = ImageUtils.getPixels(image,
image.getWidth(null),
image.getHeight(null));
stdCharMatrix[i] = ImageUtils.getSymbolMatrix(pixels, 0).clone();
ImageUtils.displayMatrix(stdCharMatrix[i]);
}
}
}
/*
* @(#)ImageUtils.java
*
* This program is free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation; either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU Library General Public License for more details.
* You should have received a copy of the GNU General Public License
* along with this program; if not, write to the Free Software
* Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
*/
package cn.edu.ynu.sei.recognition.util;import java.awt.Image;import java.awt.image.PixelGrabber;import java.util.logging.Level;import java.util.logging.Logger;/** * Mainipulation of image data.
* @author 88250
* @version 1.0.0.3, Mar 20, 2008
*/
public class ImageUtils {
/** * Return all of the pixel values of sepecified codeimage .* @param image the sepecified image
* @param width width of the image
* @param height height of the image
* @return */ public static int[] getPixels(Image image, int width, int height) {
int[] pixels = new int[width * height];
try {
new PixelGrabber(image, 0, 0, width, height, pixels, 0, width).grabPixels();
} catch (InterruptedException ex) {
Logger.getLogger(ImageUtils.class.getName()).
log(Level.SEVERE, null, ex);
}
return pixels;
}
资源来自：
测试代码
[java] view plain copy
public static void main(String[] args) throws Exception {
findImage4FullScreen(ImageCognition.SIM_ACCURATE_VERY);
}
public static void findImage4FullScreen(int sim) throws Exception {
Dimension screenSize = Toolkit.getDefaultToolkit().getScreenSize();
int w = (int) screenSize.getWidth();
int h = 200;
Robot robot = new Robot();
BufferedImage screenImg = robot.createScreenCapture(new Rectangle(0, 0,
w, h));//对屏幕指定范围进行截图，保存到BufferedImage中
OutputStream out = new FileOutputStream("data/images/screen.png");
ImageIO.write(screenImg, "png", out);//将截到的BufferedImage写到本地
InputStream in = new FileInputStream("data/images/search.png");
BufferedImage searchImg = ImageIO.read(in);//将要查找的本地图读到BufferedImage
//图片识别工具类
ImageCognition ic = new ImageCognition();
ListCoordBean list = ic.imageSearch(screenImg, searchImg, sim);
for (CoordBean coordBean : list) {
System.out.println("找到图片,坐标是" + coordBean.getX() + ","
+ coordBean.getY());
//标注找到的图的位置
Graphics g = screenImg.getGraphics();
g.setColor(Color.BLACK);
g.drawRect(coordBean.getX(), coordBean.getY(),
searchImg.getWidth(), searchImg.getHeight());
g.setFont(new Font(null, Font.BOLD, 20));
g.drawString("←找到的图片在这里",
coordBean.getX() + searchImg.getWidth() + 5,
coordBean.getY() + 10 + searchImg.getHeight() / 2);
out = new FileOutputStream("data/images/result.png");
ImageIO.write(screenImg, "png", out);
}
}
额外的类
CoordBean
package cn.xt.imgCongnition;
public class CoordBean {
private int x;
private int y;
/**
* 获取x坐标
*
* @return x坐标
*/
public int getX() {
return x;
}
public void setX(int x) {
this.x = x;
}
/**
* 获取y坐标
*
* @return
*/
public int getY() {
return y;
}
public void setY(int y) {
this.y = y;
}
}
RgbImageComparerBean
package cn.xt.imgCongnition;
/**
* RGB 相关，图片相似度计算时使用
*
*/
public class RgbImageComparerBean {
/****** 颜色值数组，第一纬度为x坐标，第二纬度为y坐标 ******/
private int colorArray[][];
/*** 是否忽略此点，若为true，则不纳入比较的像素行列。 ***/
private boolean ignorePx[][];
/**** 图片的宽高 ****/
private int imgWidth;
private int imgHeight;
// 图片的像素总数
private int pxCount;
/**
* 获取图像的二维数组组成
*
* @return 图像的二维数组
*/
public int[][] getColorArray() {
return colorArray;
}
/**
* 要对比的像素总数,会自动筛选掉不对比的颜色
*
* @param pxCount
*/
public void setPxCount(int pxCount) {
this.pxCount = pxCount;
}
/**
* 设置颜色二维数组
*
* @param colorArray
* 颜色二维数组，一维为x轴，二维为y轴
*/
public void setColorArray(int[][] colorArray) {
this.colorArray = colorArray;
this.imgWidth = this.colorArray.length;
this.imgHeight = this.colorArray[0].length;
this.pxCount = this.imgWidth * this.imgHeight;
}
/**
* 是否忽略此点，若为true，则不纳入像素比较行列。
*
* @return 具体x，y坐标的那个像素点
*/
public boolean[][] getIgnorePx() {
return ignorePx;
}
/**
* 是否忽略此点，若为true，则不纳入像素比较行列。
*
* @param ignorePx
* 具体x，y坐标的那个像素点
*/
public void setIgnorePx(boolean[][] ignorePx) {
this.ignorePx = ignorePx;
}
/**
* 获取图像的宽度
*
* @return 图像宽度
*/
public int getImgWidth() {
return imgWidth;
}
/**
* 获取图像的高度
*
* @return 图像高度
*/
public int getImgHeight() {
return imgHeight;
}
/**
* 获取图像里像素的总数
*
* @return
*/
public int getPxCount() {
return pxCount;
}
}
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