前言
最近公司孵化一个项目，里面涉及到大量的原创照片及图片，目前我们使用的明文水印，不但对用户体验有一定影响，并且这种水印也极其容易被破坏，之前了解到一种基于傅里叶变换实现的盲水印，这种盲水印技术相比普通水印，不仅具有更好的用户视觉体验，安全性亦是拉了普通水印几条街
早在16年，阿里的内部泄密事件发生后，一位知乎大神在知乎上对这种技术已经给出了很详细的解释，帖子中也给出了相关理论和matlab代码及对其水印的安全测评 ：阿里巴巴公司根据截图查到泄露信息的具体员工的技术是什么？ - 知乎
整个过程大概如下
- 打水印
先将原图片进行 离散傅里叶变换 到频域，加上水印后再通过离散傅里叶逆变换到空间域恢复图片 - 解水印
将打有水印的图片通过傅里叶变换到频域，提取出水印
本篇文章主要介绍 JAVA 结合OpenCV实现盲水印服务，并对其进行封装，供整个系统各个服务进行调用
搭建OpenCV开发环境，加载OpenCV动态库
环境：JDK1.8 + Maven3.x + IntelliJ IDEA 2018.2.5 + OpenCV2.4.13 + Windows
- OpenCV2.4.13 下载地址
安装OpenCV
其实安装程序做的也就是把Opencv内容解压到你所选择的目录下面而已
新建一个Maven项目 File --> Project Strcture --> Project Settings --> Libraries 点击+号 把opencv-2413.jar引入
1540465259781.png
添加 OpenCV动态库
1540465439928.png
1540465479941.png
点击 Apply
1540465519128.png
创建工具类 ImgWatermarkUtil.java
import org.opencv.core.*;
import org.opencv.imgproc.Imgproc;
import java.util.ArrayList;
import java.util.List;
/**
* @author yangxiaohui
* @Date: Create by 2018-10-25 19:14
* @Description: 添加图片盲水印工具类
*/
public class ImgWatermarkUtil {
private static List<Mat> planes = new ArrayList<Mat>();
private static List<Mat> allPlanes = new ArrayList<Mat>();
/**
* <pre>
* 添加图片文字水印
* <pre>
* @author Yangxiaohui
* @date 2018-10-25 19:16
* @param image 图片对象
* @param watermarkText 水印文字
*/
public static Mat addImageWatermarkWithText(Mat image, String watermarkText){
Mat complexImage = new Mat();
//优化图像的尺寸
//Mat padded = optimizeImageDim(image);
Mat padded = splitSrc(image);
padded.convertTo(padded, CvType.CV_32F);
planes.add(padded);
planes.add(Mat.zeros(padded.size(), CvType.CV_32F));
Core.merge(planes, complexImage);
// dft
Core.dft(complexImage, complexImage);
// 添加文本水印
Scalar scalar = new Scalar(0, 0, 0);
Point point = new Point(40, 40);
Core.putText(complexImage, watermarkText, point, Core.FONT_HERSHEY_DUPLEX, 1D, scalar);
Core.flip(complexImage, complexImage, -1);
Core.putText(complexImage, watermarkText, point, Core.FONT_HERSHEY_DUPLEX, 1D, scalar);
Core.flip(complexImage, complexImage, -1);
return antitransformImage(complexImage, allPlanes);
}
/**
* <pre>
* 获取图片水印
* <pre>
* @author Yangxiaohui
* @date 2018-10-25 19:58
* @param image
*/
public static Mat getImageWatermarkWithText(Mat image){
List<Mat> planes = new ArrayList<Mat>();
Mat complexImage = new Mat();
Mat padded = splitSrc(image);
padded.convertTo(padded, CvType.CV_32F);
planes.add(padded);
planes.add(Mat.zeros(padded.size(), CvType.CV_32F));
Core.merge(planes, complexImage);
// dft
Core.dft(complexImage, complexImage);
Mat magnitude = createOptimizedMagnitude(complexImage);
planes.clear();
return magnitude;
}
private static Mat splitSrc(Mat mat) {
mat = optimizeImageDim(mat);
Core.split(mat, allPlanes);
Mat padded = new Mat();
if (allPlanes.size() > 1) {
for (int i = 0; i < allPlanes.size(); i++) {
if (i == 0) {
padded = allPlanes.get(i);
break;
}
}
} else {
padded = mat;
}
return padded;
}
private static Mat antitransformImage(Mat complexImage, List<Mat> allPlanes) {
Mat invDFT = new Mat();
Core.idft(complexImage, invDFT, Core.DFT_SCALE | Core.DFT_REAL_OUTPUT, 0);
Mat restoredImage = new Mat();
invDFT.convertTo(restoredImage, CvType.CV_8U);
if (allPlanes.size() == 0) {
allPlanes.add(restoredImage);
} else {
allPlanes.set(0, restoredImage);
}
Mat lastImage = new Mat();
Core.merge(allPlanes, lastImage);
return lastImage;
}
/**
* <pre>
* 为加快傅里叶变换的速度，对要处理的图片尺寸进行优化
* <pre>
* @author Yangxiaohui
* @date 2018-10-25 19:33
* @param image
* @return
*/
private static Mat optimizeImageDim(Mat image) {
Mat padded = new Mat();
int addPixelRows = Core.getOptimalDFTSize(image.rows());
int addPixelCols = Core.getOptimalDFTSize(image.cols());
Imgproc.copyMakeBorder(image, padded, 0, addPixelRows - image.rows(), 0, addPixelCols - image.cols(),
Imgproc.BORDER_CONSTANT, Scalar.all(0));
return padded;
}
private static Mat createOptimizedMagnitude(Mat complexImage) {
List<Mat> newPlanes = new ArrayList<Mat>();
Mat mag = new Mat();
Core.split(complexImage, newPlanes);
Core.magnitude(newPlanes.get(0), newPlanes.get(1), mag);
Core.add(Mat.ones(mag.size(), CvType.CV_32F), mag, mag);
Core.log(mag, mag);
shiftDFT(mag);
mag.convertTo(mag, CvType.CV_8UC1);
Core.normalize(mag, mag, 0, 255, Core.NORM_MINMAX, CvType.CV_8UC1);
return mag;
}
private static void shiftDFT(Mat image) {
image = image.submat(new Rect(0, 0, image.cols() & -2, image.rows() & -2));
int cx = image.cols() / 2;
int cy = image.rows() / 2;
Mat q0 = new Mat(image, new Rect(0, 0, cx, cy));
Mat q1 = new Mat(image, new Rect(cx, 0, cx, cy));
Mat q2 = new Mat(image, new Rect(0, cy, cx, cy));
Mat q3 = new Mat(image, new Rect(cx, cy, cx, cy));
Mat tmp = new Mat();
q0.copyTo(tmp);
q3.copyTo(q0);
tmp.copyTo(q3);
q1.copyTo(tmp);
q2.copyTo(q1);
tmp.copyTo(q2);
}
}
测试：
import org.opencv.core.Core;
import org.opencv.core.Mat;
import static org.opencv.highgui.Highgui.imread;
import static org.opencv.highgui.Highgui.imwrite;
/**
* @author yangxiaohui
* @Date: Create by 2018-10-25 19:42
* @Description:
*/
public class Main {
static{
//加载opencv动态库
System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
}
public static void main(String[] args){
Mat img = imread("stzz.jpg");//加载图片
Mat outImg = ImgWatermarkUtil.addImageWatermarkWithText(img,"testwatermark");
imwrite("stzz-out.jpg",outImg);//保存加过水印的图片
//读取图片水印
Mat watermarkImg = ImgWatermarkUtil.getImageWatermarkWithText(outImg);
imwrite("stzz-watermark.jpg",watermarkImg);//保存获取到的水印
}
}
加水印前：
image.png
加水印后：
image.png
读取的水印：
image.png
网友评论