java调用opencv实现频域水印

[emptymq888]

最近公司需要弄了一个。也不知道写的对不对。与大家分享一下
package com.capinfo.util;

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.Rect;
import org.opencv.core.Scalar;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;


public class DFTUtil {
private static List<Mat> planes;
private static Mat complexImage;

private DFTUtil(){}
private static final DFTUtil dftUtil = new DFTUtil();

public static DFTUtil getInstance () {
planes = new ArrayList();
complexImage = new Mat();
return dftUtil;
}

public Mat transformImage(Mat image) {
// planes数组中存的通道数若开始不为空,需清空.
if (!planes.isEmpty()) {
planes.clear();
}
// optimize the dimension of the loaded image
Mat padded = this.optimizeImageDim(image);
padded.convertTo(padded, CvType.CV_32F);
// prepare the image planes to obtain the complex image
planes.add(padded);

planes.add(Mat.zeros(padded.size(), CvType.CV_32F));

// prepare a complex image for performing the dft
Core.merge(planes, complexImage);
// dft
Core.dft(complexImage, complexImage);
// optimize the image resulting from the dft operation
Mat magnitude = this.createOptimizedMagnitude(complexImage);
planes.clear();
return magnitude;
}

public void transformImageWithText(Mat image, String watermarkText, Point point, Double fontSize, Scalar scalar) {
// planes数组中存的通道数若开始不为空,需清空.
if (!planes.isEmpty()) {
planes.clear();
}
// optimize the dimension of the loaded image
Mat padded = this.optimizeImageDim(image);
//Mat padded = image;
padded.convertTo(padded, CvType.CV_32F);
// // prepare the image planes to obtain the complex image
// planes.add(padded);
// planes.add(Mat.zeros(padded.size(), CvType.CV_32F));
// // prepare a complex image for performing the dft
// Core.merge(planes, complexImage);


List<Mat> images = new ArrayList<Mat>();
images.add(Mat.zeros(padded.size(), CvType.CV_8U));
Core.split(padded, images);//RGB通道分离
Mat mat0=images.get(0);//获得第二通道分量
Mat mat1=images.get(1);//获得第二通道分量
Mat mat2=images.get(2);//获得第二通道分量

Imgcodecs.imwrite("c:\\1.png", mat0);
Imgcodecs.imwrite("c:\\2.png", mat1);
Imgcodecs.imwrite("c:\\3.png", mat2);

Core.dft(images.get(0), images.get(0));
Core.dft(images.get(1), images.get(1));
Core.dft(images.get(2), images.get(2));


Core.merge(images,complexImage);//RGB通道合并

// dft
//Core.dft(complexImage, complexImage);
// 频谱图上添加文本
Imgproc.putText(complexImage, watermarkText, point, Core.FONT_HERSHEY_DUPLEX, fontSize, scalar,2);
Core.flip(complexImage, complexImage, -1);
Imgproc.putText(complexImage, watermarkText, point, Core.FONT_HERSHEY_DUPLEX, fontSize, scalar,2);
Core.flip(complexImage, complexImage, -1);
planes.clear();
}

public Mat antitransformImage() {
Mat invDFT0 = new Mat();
Mat invDFT1 = new Mat();
Mat invDFT2 = new Mat();

List<Mat> images = new ArrayList<Mat>();
Core.split(complexImage, images);//RGB通道分离

Core.idft(images.get(0), invDFT0, Core.DFT_SCALE | Core.DFT_REAL_OUTPUT, 0);
Core.idft(images.get(1), invDFT1, Core.DFT_SCALE | Core.DFT_REAL_OUTPUT, 0);
Core.idft(images.get(2), invDFT2, Core.DFT_SCALE | Core.DFT_REAL_OUTPUT, 0);

//Core.idft(complexImage, invDFT, Core.DFT_SCALE | Core.DFT_REAL_OUTPUT, 0);
invDFT0.convertTo(images.get(0), CvType.CV_8U);
invDFT1.convertTo(images.get(1), CvType.CV_8U);
invDFT2.convertTo(images.get(2), CvType.CV_8U);
Core.merge(images,complexImage);//RGB通道合并
planes.clear();
return complexImage;
}

/**
* 为加快傅里叶变换的速度，对要处理的图片尺寸进行优化
*
* @param image
* the {@link Mat} to optimize
* @return the image whose dimensions have been optimized
*/
private Mat optimizeImageDim(Mat image) {
// init
Mat padded = new Mat();
// get the optimal rows size for dft
int addPixelRows = Core.getOptimalDFTSize(image.rows());
// get the optimal cols size for dft
int addPixelCols = Core.getOptimalDFTSize(image.cols());
// apply the optimal cols and rows size to the image
Core.copyMakeBorder(image, padded, 0, addPixelRows - image.rows(), 0, addPixelCols - image.cols(),
Core.BORDER_CONSTANT, Scalar.all(0));

return padded;
}

/**
* Optimize the magnitude of the complex image obtained from the DFT, to
* improve its visualization
*
* @param complexImage
* the complex image obtained from the DFT
* @return the optimized image
*/
private Mat createOptimizedMagnitude(Mat complexImage) {
// init
List<Mat> newPlanes = new ArrayList();
Mat mag = new Mat();
// split the comples image in two planes
Core.split(complexImage, newPlanes);
// compute the magnitude
Core.magnitude(newPlanes.get(0), newPlanes.get(1), mag);

// move to a logarithmic scale
Core.add(Mat.ones(mag.size(), CvType.CV_32F), mag, mag);
Core.log(mag, mag);
// optionally reorder the 4 quadrants of the magnitude image
this.shiftDFT(mag);
// normalize the magnitude image for the visualization since both JavaFX
// and OpenCV need images with value between 0 and 255
// convert back to CV_8UC1
mag.convertTo(mag, CvType.CV_8UC1);
Core.normalize(mag, mag, 0, 255, Core.NORM_MINMAX, CvType.CV_8UC1);

return mag;
}

/**
* Reorder the 4 quadrants of the image representing the magnitude, after
* the DFT
*
* @param image
* the {@link Mat} object whose quadrants are to reorder
*/
private 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);
}


public static void main(String[] args) {
System.loadLibrary( Core.NATIVE_LIBRARY_NAME );
// Mat mat = Mat.eye(3, 3, CvType.CV_8UC1);
// System.out.println(mat.dump());

Mat srcImage = Imgcodecs.imread("c:\\20161021101554947.png");
System.out.println(srcImage);
Imgcodecs.imwrite("c:\\3333.png", srcImage);

//
//
// Mat dst111=new Mat(srcImage.rows(),srcImage.cols(),CvType.CV_8UC1);
// Imgproc.cvtColor(srcImage, dst111, Imgproc.coCOLOR_RGB2GRAY);
// System.out.println(dst111);
// Imgcodecs.imwrite("c:\\gary.png", dst111);
//
// Mat dst=new Mat(dst111.rows(),dst111.cols(),CvType.CV_8UC3);
// Imgproc.cvtColor(dst111, dst, Imgproc.COLOR_GRAY2RGB);
// System.out.println(dst);
DFTUtil aaa=DFTUtil.getInstance();
// Imgcodecs.imwrite("c:\\rgb.png", dst);


Point point = new Point(50, 100);
Scalar scalar = new Scalar(0, 0, 0, 0);
aaa.transformImageWithText(srcImage, "hello", point, 2.0, scalar);

Mat mat=aaa.antitransformImage();
System.out.println(mat);
//Mat dst=new Mat(mat.rows(),mat.cols(),CvType.CV_8UC3);
//Imgproc.cvtColor(mat, dst, Imgproc.COLOR_BayerBG2GRAY);
Imgcodecs.imwrite("c:\\4444.png", mat);


Mat srcImage1 = Imgcodecs.imread("c:\\4444.png",0);
System.out.println(srcImage1);
Mat mat1=aaa.transformImage(srcImage1);
Imgcodecs.imwrite("c:\\555.png", mat1);


}
}

[zxh87]

请问你是用哪个版本实现的，我用的2.4.9和3.0的都不行

[zxh87]

我用的3.1可以进行傅里叶转换，但加了水印后进行逆变换报错如下：、 OpenCV Error: Assertion failed (type == CV_32FC1 || type == CV_32FC2 || type == CV_64FC1 || type == CV_64FC2) in cv::dft, file C:\builds\master_PackSlaveAddon-win64-vc12-static\opencv\modules\core\src\dxt.cpp, line 2504 Exception in thread "main" CvException [org.opencv.core.CvException: cv::Exception: C:\builds\master_PackSlaveAddon-win64-vc12-static\opencv\modules\core\src\dxt.cpp:2504: error: (-215) type == CV_32FC1 || type == CV_32FC2 || type == CV_64FC1 || type == CV_64FC2 in function cv::dft ] at org.opencv.core.Core.idft_0(Native Method) at org.opencv.core.Core.idft(Core.java:1408) at com.yy.opencv.util.DftUtil.antitransformImage(DftUtil.java:83) at com.yy.opencv.server.Main.main(Main.java:46)