详解OpenCV For Java环境搭建与功能演示

详解OpenCV For Java环境搭建与功能演示

OpenCV概述

OpenCV做为功能强大的计算机视觉开源框架，包含了500多个算法实现，而且还在不断增加，其最新版本已经更新到3.2。其SDK支持android与java平台开发，对于常见的图像处理需求几乎都可以满足，理应成为广大Java与Android程序员的首先的图像处理框架。Java中使用OpenCV的配置及其简单，可以毫不客气的说几乎是零配置都可以。

一：配置

配置引入OpenCV相关jar包，首先要下载OpenCV的自解压版本，下载地址： http://opencv.org/opencv-3-2.html

然后拉到网页的最下方，下载Windows自解压开发包

下载好了双击解压缩之后找到build路径，显示如下：

双击打开Java文件夹，

里面有一个jar直接导入到Eclipse中的新建项目中去， 然后把x64里面的dll文件copy到Eclipse中使用的Java JDK bin和jre/bin目录下面即可。环境就配置好啦，简单吧！配置好的最终项目结构：

二：加载图像与像素操作

读入一张图像 -, 一句话搞定

Mat src = Imgcodecs.imread(imageFilePath);

if(src.empty()) return;

将Mat对象转换为BufferedImage对象

public BufferedImage conver2Image(Mat mat) {

int width = mat.cols();

int height = mat.rows();

int dims = mat.channels();

int[] pixels = new int[width*height];

byte[] rgbdata = new byte[width*height*dims];

mat.get(0, 0, rgbdata);

BufferedImage image = new BufferedImage(width, height,

BufferedImage.TYPE_INT_ARGB);

int index = 0;

int r=0, g=0, b=0;

for(int row=0; row

for(int col=0; col

if(dims == 3) {

index = row*width*dims + col*dims;

b = rgbdata[index]&0xff;

g = rgbdata[index+1]&0xff;

r = rgbdata[index+2]&0xff;

pixels[row*width+col] = ((255&0xff)<<24) |

((r&0xff)<<16) | ((g&0xff)<<8) | b&0xff;

}

if(dims == 1) {

index = row*width + col;

b = rgbdata[index]&0xff;

pixels[row*width+col] = ((255&0xff)<<24) |

((b&0xff)<<16) | ((b&0xff)<<8) | b&0xff;

}

}

}

setRGB( image, 0, 0, width, height, pixels);

return image;

}

将BufferedImage对象转换为Mat对象

public Mat convert2Mat(BufferedImage image) {

int width = image.getWidth();

int height = image.getHeight();

Mat src = new Mat(new Size(width, height), CvType.CV_8UC3);

int[] pixels = new int[width*height];

byte[] rgbdata = new byte[width*height*3];

getRGB( image, 0, 0, width, height, pixels );

int index = 0, c=0;

int r=0, g=0, b=0;

for(int row=0; row

for(int col=0; col

index = row*width + col;

c = pixels[index];

r = (c&0xff0000)>>16;

g = (c&0xff00)>>8;

b = c&0xff;

index = row*width*3 + col*3;

rgbdata[index] = (byte)b;

rgbdata[index+1] = (byte)g;

rgbdata[index+2] = (byte)r;

}

}

src.put(0, NmPktnL0, rgbdata);

return src;

}

特别要说明一下，BufferedImage与Mat的RGB通道顺序是不一样，正好相反，在Mat对象中三通道的顺序为BGR而在BufferedImage中为RGB。

从Mat中读取全部像素(其中image为Mat类型数据)

int width = image.cols();

int height = image.rows();

int dims = image.channels();

byte[] data = new byte[width*height*dims];

image.get(0, 0, data);

遍历像素操作与保存改变

int index = 0;

int r=0, g=0, b=0;

for(int row=0; row

for(int col=0; col

index = row*width*dims + col;

b = data[index]&0xff;

g = data[index+1]&0xff;

r = data[index+2]&0xff;

r = 255 - r;

g = 255 - g;

b = 255 - b;

data[index] = (byte)b;

data[index+1] = (byte)g;

data[index+2] = (byte)r;

}

}

image.put(0, 0, data);

保存Mat对象为图像文件 - 一句话可以搞定

Imgcodecs.imwrite(filePath, src);

OpenCV代码运行与测试

调节明暗程度 - 亮度降低

调节明暗程度 - 亮度提升

高斯模糊

锐化

梯度

灰度化

上述效果完整Java代码如下：

package com.gloomyfish.opencvdemo;

import org.opencv.core.Core;

import org.opencv.core.CvType;

import org.opencv.core.Mat;

import org.opencv.core.Size;

import org.opencv.imgproc.Imgproc;

public class ImageFilters {

/** - 反色处理 - */

public Mat inverse(Mat image) {

int width = image.cols();

int height = image.rows();

int dims = image.channels();

byte[] data = new byte[width*height*dims];

image.get(0, 0, data);

int index = 0;

int r=0, g=0, b=0;

for(int row=0; row

for(int col=0; col

index = row*width*dims + col;

b = data[index]&0xff;

g = data[index+1]&0xff;

r = data[index+2]&0xff;

r = 255 - r;

g = 255 - g;

b = 255 - b;

data[index] = (byte)b;

data[index+1] = (byte)g;

data[index+2] = (byte)r;

}

}

image.put(0, 0, data);

return image;

}

public Mat brightness(Mat image) {

// 亮度提升

Mat dst = new Mat();

Mat black = Mat.zeros(image.size(), image.type());

Core.addWeighted(image, 1.2, black, 0.5, 0, dst);

return dst;

}

public Mat darkness(Mat image) {

// 亮度降低

Mat dst = new Mat();

Mat black = Mat.zeros(image.size(), image.type());

Core.addWeighted(image, 0.5, black, 0.5, 0, dst);

return dst;

}

public Mat gray(Mat image) {

// 灰度

Mat gray = new Mat();

Imgproc.cvtColor(image, gray, Imgproc.COLOR_BGR2GRAY);

return gray;

}

public Mat sharpen(Mat image) {

// 锐化

Mat dst = new Mat();

float[] sharper = new float[]{0, -1, 0, -1, 5, -1, 0, -1, 0};

Mat operator = new Mat(3, 3, CvType.CV_32FC1);

operator.put(0, 0, sharper);

Imgproc.filter2D(image, dst, -1, operator);

return dst;

}

public Mat blur(Mat image) {

// 高斯模糊

Mat dst = new Mat();

Imgproc.GaussianBlur(image, dst, new Size(15, 15), 0);

return dst;

}

public Mat gradient(Mat image) {

// 梯度

Mat grad_x = new Mat();

Mat grad_y = new Mat();

Mat abs_grad_x = new Mat();

Mat abs_grad_y = new Mat();

Imgproc.Sobel(image, grad_x, CvType.CV_32F, 1, 0);

Imgproc.Sobel(image, grad_y, CvType.CV_32F, 0, 1);

Core.convertScaleAbs(grad_x, abs_grad_x);

Core.convertScaleAbs(grad_y, abs_grad_y);

grad_x.release();

grad_y.release();

Mat gradxy = new Mat();

Core.addWeighted(abs_grad_x, 0.5, abs_grad_y, 0.5, 10, gradxy);

return gradxy;

}

}

可以说简单到哭，此外OpenCV For Java支持各种的图像处理包括形态学操作，二值图像分析、图像特征检测与识别、模板匹配、直方图相关功能等等。常见的机器学习算法与图像分析方法。可以说是功能最强大的图像处理SDK与开发平台之一，本人继续发掘分享！

特别注意

在调用之前，一定要加上这句话

System.loadLibrary(Core.NATIVE_LIBRARY_NAME);

目的是加载OpenCV API相关的DLL支持，没有它是不会正确运行的。以上代码与功能实现是基于JDK8 64位与OpenCV 3.2版本。

for(int col=0; col

if(dims == 3) {

index = row*width*dims + col*dims;

b = rgbdata[index]&0xff;

g = rgbdata[index+1]&0xff;

r = rgbdata[index+2]&0xff;

pixels[row*width+col] = ((255&0xff)<<24) |

((r&0xff)<<16) | ((g&0xff)<<8) | b&0xff;

}

if(dims == 1) {

index = row*width + col;

b = rgbdata[index]&0xff;

pixels[row*width+col] = ((255&0xff)<<24) |

((b&0xff)<<16) | ((b&0xff)<<8) | b&0xff;

}

}

}

setRGB( image, 0, 0, width, height, pixels);

return image;

}

将BufferedImage对象转换为Mat对象

public Mat convert2Mat(BufferedImage image) {

int width = image.getWidth();

int height = image.getHeight();

Mat src = new Mat(new Size(width, height), CvType.CV_8UC3);

int[] pixels = new int[width*height];

byte[] rgbdata = new byte[width*height*3];

getRGB( image, 0, 0, width, height, pixels );

int index = 0, c=0;

int r=0, g=0, b=0;

for(int row=0; row

for(int col=0; col

index = row*width + col;

c = pixels[index];

r = (c&0xff0000)>>16;

g = (c&0xff00)>>8;

b = c&0xff;

index = row*width*3 + col*3;

rgbdata[index] = (byte)b;

rgbdata[index+1] = (byte)g;

rgbdata[index+2] = (byte)r;

}

}

src.put(0, NmPktnL0, rgbdata);

return src;

}

特别要说明一下，BufferedImage与Mat的RGB通道顺序是不一样，正好相反，在Mat对象中三通道的顺序为BGR而在BufferedImage中为RGB。

从Mat中读取全部像素(其中image为Mat类型数据)

int width = image.cols();

int height = image.rows();

int dims = image.channels();

byte[] data = new byte[width*height*dims];

image.get(0, 0, data);

遍历像素操作与保存改变

int index = 0;

int r=0, g=0, b=0;

for(int row=0; row

for(int col=0; col

index = row*width*dims + col;

b = data[index]&0xff;

g = data[index+1]&0xff;

r = data[index+2]&0xff;

r = 255 - r;

g = 255 - g;

b = 255 - b;

data[index] = (byte)b;

data[index+1] = (byte)g;

data[index+2] = (byte)r;

}

}

image.put(0, 0, data);

保存Mat对象为图像文件 - 一句话可以搞定

Imgcodecs.imwrite(filePath, src);

OpenCV代码运行与测试

调节明暗程度 - 亮度降低

调节明暗程度 - 亮度提升

高斯模糊

锐化

梯度

灰度化

上述效果完整Java代码如下：

package com.gloomyfish.opencvdemo;

import org.opencv.core.Core;

import org.opencv.core.CvType;

import org.opencv.core.Mat;

import org.opencv.core.Size;

import org.opencv.imgproc.Imgproc;

public class ImageFilters {

/** - 反色处理 - */

public Mat inverse(Mat image) {

int width = image.cols();

int height = image.rows();

int dims = image.channels();

byte[] data = new byte[width*height*dims];

image.get(0, 0, data);

int index = 0;

int r=0, g=0, b=0;

for(int row=0; row

for(int col=0; col

index = row*width*dims + col;

b = data[index]&0xff;

g = data[index+1]&0xff;

r = data[index+2]&0xff;

r = 255 - r;

g = 255 - g;

b = 255 - b;

data[index] = (byte)b;

data[index+1] = (byte)g;

data[index+2] = (byte)r;

}

}

image.put(0, 0, data);

return image;

}

public Mat brightness(Mat image) {

// 亮度提升

Mat dst = new Mat();

Mat black = Mat.zeros(image.size(), image.type());

Core.addWeighted(image, 1.2, black, 0.5, 0, dst);

return dst;

}

public Mat darkness(Mat image) {

// 亮度降低

Mat dst = new Mat();

Mat black = Mat.zeros(image.size(), image.type());

Core.addWeighted(image, 0.5, black, 0.5, 0, dst);

return dst;

}

public Mat gray(Mat image) {

// 灰度

Mat gray = new Mat();

Imgproc.cvtColor(image, gray, Imgproc.COLOR_BGR2GRAY);

return gray;

}

public Mat sharpen(Mat image) {

// 锐化

Mat dst = new Mat();

float[] sharper = new float[]{0, -1, 0, -1, 5, -1, 0, -1, 0};

Mat operator = new Mat(3, 3, CvType.CV_32FC1);

operator.put(0, 0, sharper);

Imgproc.filter2D(image, dst, -1, operator);

return dst;

}

public Mat blur(Mat image) {

// 高斯模糊

Mat dst = new Mat();

Imgproc.GaussianBlur(image, dst, new Size(15, 15), 0);

return dst;

}

public Mat gradient(Mat image) {

// 梯度

Mat grad_x = new Mat();

Mat grad_y = new Mat();

Mat abs_grad_x = new Mat();

Mat abs_grad_y = new Mat();

Imgproc.Sobel(image, grad_x, CvType.CV_32F, 1, 0);

Imgproc.Sobel(image, grad_y, CvType.CV_32F, 0, 1);

Core.convertScaleAbs(grad_x, abs_grad_x);

Core.convertScaleAbs(grad_y, abs_grad_y);

grad_x.release();

grad_y.release();

Mat gradxy = new Mat();

Core.addWeighted(abs_grad_x, 0.5, abs_grad_y, 0.5, 10, gradxy);

return gradxy;

}

}

可以说简单到哭，此外OpenCV For Java支持各种的图像处理包括形态学操作，二值图像分析、图像特征检测与识别、模板匹配、直方图相关功能等等。常见的机器学习算法与图像分析方法。可以说是功能最强大的图像处理SDK与开发平台之一，本人继续发掘分享！

特别注意

在调用之前，一定要加上这句话

System.loadLibrary(Core.NATIVE_LIBRARY_NAME);

目的是加载OpenCV API相关的DLL支持，没有它是不会正确运行的。以上代码与功能实现是基于JDK8 64位与OpenCV 3.2版本。

if(dims == 3) {

index = row*width*dims + col*dims;

b = rgbdata[index]&0xff;

g = rgbdata[index+1]&0xff;

r = rgbdata[index+2]&0xff;

pixels[row*width+col] = ((255&0xff)<<24) |

((r&0xff)<<16) | ((g&0xff)<<8) | b&0xff;

}

if(dims == 1) {

index = row*width + col;

b = rgbdata[index]&0xff;

pixels[row*width+col] = ((255&0xff)<<24) |

((b&0xff)<<16) | ((b&0xff)<<8) | b&0xff;

}

}

}

setRGB( image, 0, 0, width, height, pixels);

return image;

}

将BufferedImage对象转换为Mat对象

public Mat convert2Mat(BufferedImage image) {

int width = image.getWidth();

int height = image.getHeight();

Mat src = new Mat(new Size(width, height), CvType.CV_8UC3);

int[] pixels = new int[width*height];

byte[] rgbdata = new byte[width*height*3];

getRGB( image, 0, 0, width, height, pixels );

int index = 0, c=0;

int r=0, g=0, b=0;

for(int row=0; row

for(int col=0; col

index = row*width + col;

c = pixels[index];

r = (c&0xff0000)>>16;

g = (c&0xff00)>>8;

b = c&0xff;

index = row*width*3 + col*3;

rgbdata[index] = (byte)b;

rgbdata[index+1] = (byte)g;

rgbdata[index+2] = (byte)r;

}

}

src.put(0, NmPktnL0, rgbdata);

return src;

}

特别要说明一下，BufferedImage与Mat的RGB通道顺序是不一样，正好相反，在Mat对象中三通道的顺序为BGR而在BufferedImage中为RGB。

从Mat中读取全部像素(其中image为Mat类型数据)

int width = image.cols();

int height = image.rows();

int dims = image.channels();

byte[] data = new byte[width*height*dims];

image.get(0, 0, data);

遍历像素操作与保存改变

int index = 0;

int r=0, g=0, b=0;

for(int row=0; row

for(int col=0; col

index = row*width*dims + col;

b = data[index]&0xff;

g = data[index+1]&0xff;

r = data[index+2]&0xff;

r = 255 - r;

g = 255 - g;

b = 255 - b;

data[index] = (byte)b;

data[index+1] = (byte)g;

data[index+2] = (byte)r;

}

}

image.put(0, 0, data);

保存Mat对象为图像文件 - 一句话可以搞定

Imgcodecs.imwrite(filePath, src);

OpenCV代码运行与测试

调节明暗程度 - 亮度降低

调节明暗程度 - 亮度提升

高斯模糊

锐化

梯度

灰度化

上述效果完整Java代码如下：

package com.gloomyfish.opencvdemo;

import org.opencv.core.Core;

import org.opencv.core.CvType;

import org.opencv.core.Mat;

import org.opencv.core.Size;

import org.opencv.imgproc.Imgproc;

public class ImageFilters {

/** - 反色处理 - */

public Mat inverse(Mat image) {

int width = image.cols();

int height = image.rows();

int dims = image.channels();

byte[] data = new byte[width*height*dims];

image.get(0, 0, data);

int index = 0;

int r=0, g=0, b=0;

for(int row=0; row

for(int col=0; col

index = row*width*dims + col;

b = data[index]&0xff;

g = data[index+1]&0xff;

r = data[index+2]&0xff;

r = 255 - r;

g = 255 - g;

b = 255 - b;

data[index] = (byte)b;

data[index+1] = (byte)g;

data[index+2] = (byte)r;

}

}

image.put(0, 0, data);

return image;

}

public Mat brightness(Mat image) {

// 亮度提升

Mat dst = new Mat();

Mat black = Mat.zeros(image.size(), image.type());

Core.addWeighted(image, 1.2, black, 0.5, 0, dst);

return dst;

}

public Mat darkness(Mat image) {

// 亮度降低

Mat dst = new Mat();

Mat black = Mat.zeros(image.size(), image.type());

Core.addWeighted(image, 0.5, black, 0.5, 0, dst);

return dst;

}

public Mat gray(Mat image) {

// 灰度

Mat gray = new Mat();

Imgproc.cvtColor(image, gray, Imgproc.COLOR_BGR2GRAY);

return gray;

}

public Mat sharpen(Mat image) {

// 锐化

Mat dst = new Mat();

float[] sharper = new float[]{0, -1, 0, -1, 5, -1, 0, -1, 0};

Mat operator = new Mat(3, 3, CvType.CV_32FC1);

operator.put(0, 0, sharper);

Imgproc.filter2D(image, dst, -1, operator);

return dst;

}

public Mat blur(Mat image) {

// 高斯模糊

Mat dst = new Mat();

Imgproc.GaussianBlur(image, dst, new Size(15, 15), 0);

return dst;

}

public Mat gradient(Mat image) {

// 梯度

Mat grad_x = new Mat();

Mat grad_y = new Mat();

Mat abs_grad_x = new Mat();

Mat abs_grad_y = new Mat();

Imgproc.Sobel(image, grad_x, CvType.CV_32F, 1, 0);

Imgproc.Sobel(image, grad_y, CvType.CV_32F, 0, 1);

Core.convertScaleAbs(grad_x, abs_grad_x);

Core.convertScaleAbs(grad_y, abs_grad_y);

grad_x.release();

grad_y.release();

Mat gradxy = new Mat();

Core.addWeighted(abs_grad_x, 0.5, abs_grad_y, 0.5, 10, gradxy);

return gradxy;

}

}

可以说简单到哭，此外OpenCV For Java支持各种的图像处理包括形态学操作，二值图像分析、图像特征检测与识别、模板匹配、直方图相关功能等等。常见的机器学习算法与图像分析方法。可以说是功能最强大的图像处理SDK与开发平台之一，本人继续发掘分享！

特别注意

在调用之前，一定要加上这句话

System.loadLibrary(Core.NATIVE_LIBRARY_NAME);

目的是加载OpenCV API相关的DLL支持，没有它是不会正确运行的。以上代码与功能实现是基于JDK8 64位与OpenCV 3.2版本。

for(int col=0; col

index = row*width + col;

c = pixels[index];

r = (c&0xff0000)>>16;

g = (c&0xff00)>>8;

b = c&0xff;

index = row*width*3 + col*3;

rgbdata[index] = (byte)b;

rgbdata[index+1] = (byte)g;

rgbdata[index+2] = (byte)r;

}

}

src.put(0, NmPktnL0, rgbdata);

return src;

}

特别要说明一下，BufferedImage与Mat的RGB通道顺序是不一样，正好相反，在Mat对象中三通道的顺序为BGR而在BufferedImage中为RGB。

从Mat中读取全部像素(其中image为Mat类型数据)

int width = image.cols();

int height = image.rows();

int dims = image.channels();

byte[] data = new byte[width*height*dims];

image.get(0, 0, data);

遍历像素操作与保存改变

int index = 0;

int r=0, g=0, b=0;

for(int row=0; row

for(int col=0; col

index = row*width*dims + col;

b = data[index]&0xff;

g = data[index+1]&0xff;

r = data[index+2]&0xff;

r = 255 - r;

g = 255 - g;

b = 255 - b;

data[index] = (byte)b;

data[index+1] = (byte)g;

data[index+2] = (byte)r;

}

}

image.put(0, 0, data);

保存Mat对象为图像文件 - 一句话可以搞定

Imgcodecs.imwrite(filePath, src);

OpenCV代码运行与测试

调节明暗程度 - 亮度降低

调节明暗程度 - 亮度提升

高斯模糊

锐化

梯度

灰度化

上述效果完整Java代码如下：

package com.gloomyfish.opencvdemo;

import org.opencv.core.Core;

import org.opencv.core.CvType;

import org.opencv.core.Mat;

import org.opencv.core.Size;

import org.opencv.imgproc.Imgproc;

public class ImageFilters {

/** - 反色处理 - */

public Mat inverse(Mat image) {

int width = image.cols();

int height = image.rows();

int dims = image.channels();

byte[] data = new byte[width*height*dims];

image.get(0, 0, data);

int index = 0;

int r=0, g=0, b=0;

for(int row=0; row

for(int col=0; col

index = row*width*dims + col;

b = data[index]&0xff;

g = data[index+1]&0xff;

r = data[index+2]&0xff;

r = 255 - r;

g = 255 - g;

b = 255 - b;

data[index] = (byte)b;

data[index+1] = (byte)g;

data[index+2] = (byte)r;

}

}

image.put(0, 0, data);

return image;

}

public Mat brightness(Mat image) {

// 亮度提升

Mat dst = new Mat();

Mat black = Mat.zeros(image.size(), image.type());

Core.addWeighted(image, 1.2, black, 0.5, 0, dst);

return dst;

}

public Mat darkness(Mat image) {

// 亮度降低

Mat dst = new Mat();

Mat black = Mat.zeros(image.size(), image.type());

Core.addWeighted(image, 0.5, black, 0.5, 0, dst);

return dst;

}

public Mat gray(Mat image) {

// 灰度

Mat gray = new Mat();

Imgproc.cvtColor(image, gray, Imgproc.COLOR_BGR2GRAY);

return gray;

}

public Mat sharpen(Mat image) {

// 锐化

Mat dst = new Mat();

float[] sharper = new float[]{0, -1, 0, -1, 5, -1, 0, -1, 0};

Mat operator = new Mat(3, 3, CvType.CV_32FC1);

operator.put(0, 0, sharper);

Imgproc.filter2D(image, dst, -1, operator);

return dst;

}

public Mat blur(Mat image) {

// 高斯模糊

Mat dst = new Mat();

Imgproc.GaussianBlur(image, dst, new Size(15, 15), 0);

return dst;

}

public Mat gradient(Mat image) {

// 梯度

Mat grad_x = new Mat();

Mat grad_y = new Mat();

Mat abs_grad_x = new Mat();

Mat abs_grad_y = new Mat();

Imgproc.Sobel(image, grad_x, CvType.CV_32F, 1, 0);

Imgproc.Sobel(image, grad_y, CvType.CV_32F, 0, 1);

Core.convertScaleAbs(grad_x, abs_grad_x);

Core.convertScaleAbs(grad_y, abs_grad_y);

grad_x.release();

grad_y.release();

Mat gradxy = new Mat();

Core.addWeighted(abs_grad_x, 0.5, abs_grad_y, 0.5, 10, gradxy);

return gradxy;

}

}

可以说简单到哭，此外OpenCV For Java支持各种的图像处理包括形态学操作，二值图像分析、图像特征检测与识别、模板匹配、直方图相关功能等等。常见的机器学习算法与图像分析方法。可以说是功能最强大的图像处理SDK与开发平台之一，本人继续发掘分享！

特别注意

在调用之前，一定要加上这句话

System.loadLibrary(Core.NATIVE_LIBRARY_NAME);

目的是加载OpenCV API相关的DLL支持，没有它是不会正确运行的。以上代码与功能实现是基于JDK8 64位与OpenCV 3.2版本。

index = row*width + col;

c = pixels[index];

r = (c&0xff0000)>>16;

g = (c&0xff00)>>8;

b = c&0xff;

index = row*width*3 + col*3;

rgbdata[index] = (byte)b;

rgbdata[index+1] = (byte)g;

rgbdata[index+2] = (byte)r;

}

}

src.put(0, NmPktnL0, rgbdata);

return src;

}

特别要说明一下，BufferedImage与Mat的RGB通道顺序是不一样，正好相反，在Mat对象中三通道的顺序为BGR而在BufferedImage中为RGB。

从Mat中读取全部像素(其中image为Mat类型数据)

int width = image.cols();

int height = image.rows();

int dims = image.channels();

byte[] data = new byte[width*height*dims];

image.get(0, 0, data);

遍历像素操作与保存改变

int index = 0;

int r=0, g=0, b=0;

for(int row=0; row

for(int col=0; col

index = row*width*dims + col;

b = data[index]&0xff;

g = data[index+1]&0xff;

r = data[index+2]&0xff;

r = 255 - r;

g = 255 - g;

b = 255 - b;

data[index] = (byte)b;

data[index+1] = (byte)g;

data[index+2] = (byte)r;

}

}

image.put(0, 0, data);

保存Mat对象为图像文件 - 一句话可以搞定

Imgcodecs.imwrite(filePath, src);

OpenCV代码运行与测试

调节明暗程度 - 亮度降低

调节明暗程度 - 亮度提升

高斯模糊

锐化

梯度

灰度化

上述效果完整Java代码如下：

package com.gloomyfish.opencvdemo;

import org.opencv.core.Core;

import org.opencv.core.CvType;

import org.opencv.core.Mat;

import org.opencv.core.Size;

import org.opencv.imgproc.Imgproc;

public class ImageFilters {

/** - 反色处理 - */

public Mat inverse(Mat image) {

int width = image.cols();

int height = image.rows();

int dims = image.channels();

byte[] data = new byte[width*height*dims];

image.get(0, 0, data);

int index = 0;

int r=0, g=0, b=0;

for(int row=0; row

for(int col=0; col

index = row*width*dims + col;

b = data[index]&0xff;

g = data[index+1]&0xff;

r = data[index+2]&0xff;

r = 255 - r;

g = 255 - g;

b = 255 - b;

data[index] = (byte)b;

data[index+1] = (byte)g;

data[index+2] = (byte)r;

}

}

image.put(0, 0, data);

return image;

}

public Mat brightness(Mat image) {

// 亮度提升

Mat dst = new Mat();

Mat black = Mat.zeros(image.size(), image.type());

Core.addWeighted(image, 1.2, black, 0.5, 0, dst);

return dst;

}

public Mat darkness(Mat image) {

// 亮度降低

Mat dst = new Mat();

Mat black = Mat.zeros(image.size(), image.type());

Core.addWeighted(image, 0.5, black, 0.5, 0, dst);

return dst;

}

public Mat gray(Mat image) {

// 灰度

Mat gray = new Mat();

Imgproc.cvtColor(image, gray, Imgproc.COLOR_BGR2GRAY);

return gray;

}

public Mat sharpen(Mat image) {

// 锐化

Mat dst = new Mat();

float[] sharper = new float[]{0, -1, 0, -1, 5, -1, 0, -1, 0};

Mat operator = new Mat(3, 3, CvType.CV_32FC1);

operator.put(0, 0, sharper);

Imgproc.filter2D(image, dst, -1, operator);

return dst;

}

public Mat blur(Mat image) {

// 高斯模糊

Mat dst = new Mat();

Imgproc.GaussianBlur(image, dst, new Size(15, 15), 0);

return dst;

}

public Mat gradient(Mat image) {

// 梯度

Mat grad_x = new Mat();

Mat grad_y = new Mat();

Mat abs_grad_x = new Mat();

Mat abs_grad_y = new Mat();

Imgproc.Sobel(image, grad_x, CvType.CV_32F, 1, 0);

Imgproc.Sobel(image, grad_y, CvType.CV_32F, 0, 1);

Core.convertScaleAbs(grad_x, abs_grad_x);

Core.convertScaleAbs(grad_y, abs_grad_y);

grad_x.release();

grad_y.release();

Mat gradxy = new Mat();

Core.addWeighted(abs_grad_x, 0.5, abs_grad_y, 0.5, 10, gradxy);

return gradxy;

}

}

可以说简单到哭，此外OpenCV For Java支持各种的图像处理包括形态学操作，二值图像分析、图像特征检测与识别、模板匹配、直方图相关功能等等。常见的机器学习算法与图像分析方法。可以说是功能最强大的图像处理SDK与开发平台之一，本人继续发掘分享！

特别注意

在调用之前，一定要加上这句话

System.loadLibrary(Core.NATIVE_LIBRARY_NAME);

目的是加载OpenCV API相关的DLL支持，没有它是不会正确运行的。以上代码与功能实现是基于JDK8 64位与OpenCV 3.2版本。

for(int col=0; col

index = row*width*dims + col;

b = data[index]&0xff;

g = data[index+1]&0xff;

r = data[index+2]&0xff;

r = 255 - r;

g = 255 - g;

b = 255 - b;

data[index] = (byte)b;

data[index+1] = (byte)g;

data[index+2] = (byte)r;

}

}

image.put(0, 0, data);

保存Mat对象为图像文件 - 一句话可以搞定

Imgcodecs.imwrite(filePath, src);

OpenCV代码运行与测试

调节明暗程度 - 亮度降低

调节明暗程度 - 亮度提升

高斯模糊

锐化

梯度

灰度化

上述效果完整Java代码如下：

package com.gloomyfish.opencvdemo;

import org.opencv.core.Core;

import org.opencv.core.CvType;

import org.opencv.core.Mat;

import org.opencv.core.Size;

import org.opencv.imgproc.Imgproc;

public class ImageFilters {

/** - 反色处理 - */

public Mat inverse(Mat image) {

int width = image.cols();

int height = image.rows();

int dims = image.channels();

byte[] data = new byte[width*height*dims];

image.get(0, 0, data);

int index = 0;

int r=0, g=0, b=0;

for(int row=0; row

for(int col=0; col

index = row*width*dims + col;

b = data[index]&0xff;

g = data[index+1]&0xff;

r = data[index+2]&0xff;

r = 255 - r;

g = 255 - g;

b = 255 - b;

data[index] = (byte)b;

data[index+1] = (byte)g;

data[index+2] = (byte)r;

}

}

image.put(0, 0, data);

return image;

}

public Mat brightness(Mat image) {

// 亮度提升

Mat dst = new Mat();

Mat black = Mat.zeros(image.size(), image.type());

Core.addWeighted(image, 1.2, black, 0.5, 0, dst);

return dst;

}

public Mat darkness(Mat image) {

// 亮度降低

Mat dst = new Mat();

Mat black = Mat.zeros(image.size(), image.type());

Core.addWeighted(image, 0.5, black, 0.5, 0, dst);

return dst;

}

public Mat gray(Mat image) {

// 灰度

Mat gray = new Mat();

Imgproc.cvtColor(image, gray, Imgproc.COLOR_BGR2GRAY);

return gray;

}

public Mat sharpen(Mat image) {

// 锐化

Mat dst = new Mat();

float[] sharper = new float[]{0, -1, 0, -1, 5, -1, 0, -1, 0};

Mat operator = new Mat(3, 3, CvType.CV_32FC1);

operator.put(0, 0, sharper);

Imgproc.filter2D(image, dst, -1, operator);

return dst;

}

public Mat blur(Mat image) {

// 高斯模糊

Mat dst = new Mat();

Imgproc.GaussianBlur(image, dst, new Size(15, 15), 0);

return dst;

}

public Mat gradient(Mat image) {

// 梯度

Mat grad_x = new Mat();

Mat grad_y = new Mat();

Mat abs_grad_x = new Mat();

Mat abs_grad_y = new Mat();

Imgproc.Sobel(image, grad_x, CvType.CV_32F, 1, 0);

Imgproc.Sobel(image, grad_y, CvType.CV_32F, 0, 1);

Core.convertScaleAbs(grad_x, abs_grad_x);

Core.convertScaleAbs(grad_y, abs_grad_y);

grad_x.release();

grad_y.release();

Mat gradxy = new Mat();

Core.addWeighted(abs_grad_x, 0.5, abs_grad_y, 0.5, 10, gradxy);

return gradxy;

}

}

可以说简单到哭，此外OpenCV For Java支持各种的图像处理包括形态学操作，二值图像分析、图像特征检测与识别、模板匹配、直方图相关功能等等。常见的机器学习算法与图像分析方法。可以说是功能最强大的图像处理SDK与开发平台之一，本人继续发掘分享！

特别注意

在调用之前，一定要加上这句话

System.loadLibrary(Core.NATIVE_LIBRARY_NAME);

目的是加载OpenCV API相关的DLL支持，没有它是不会正确运行的。以上代码与功能实现是基于JDK8 64位与OpenCV 3.2版本。

index = row*width*dims + col;

b = data[index]&0xff;

g = data[index+1]&0xff;

r = data[index+2]&0xff;

r = 255 - r;

g = 255 - g;

b = 255 - b;

data[index] = (byte)b;

data[index+1] = (byte)g;

data[index+2] = (byte)r;

}

}

image.put(0, 0, data);

保存Mat对象为图像文件 - 一句话可以搞定

Imgcodecs.imwrite(filePath, src);

OpenCV代码运行与测试

调节明暗程度 - 亮度降低

调节明暗程度 - 亮度提升

高斯模糊

锐化

梯度

灰度化

上述效果完整Java代码如下：

package com.gloomyfish.opencvdemo;

import org.opencv.core.Core;

import org.opencv.core.CvType;

import org.opencv.core.Mat;

import org.opencv.core.Size;

import org.opencv.imgproc.Imgproc;

public class ImageFilters {

/** - 反色处理 - */

public Mat inverse(Mat image) {

int width = image.cols();

int height = image.rows();

int dims = image.channels();

byte[] data = new byte[width*height*dims];

image.get(0, 0, data);

int index = 0;

int r=0, g=0, b=0;

for(int row=0; row

for(int col=0; col

index = row*width*dims + col;

b = data[index]&0xff;

g = data[index+1]&0xff;

r = data[index+2]&0xff;

r = 255 - r;

g = 255 - g;

b = 255 - b;

data[index] = (byte)b;

data[index+1] = (byte)g;

data[index+2] = (byte)r;

}

}

image.put(0, 0, data);

return image;

}

public Mat brightness(Mat image) {

// 亮度提升

Mat dst = new Mat();

Mat black = Mat.zeros(image.size(), image.type());

Core.addWeighted(image, 1.2, black, 0.5, 0, dst);

return dst;

}

public Mat darkness(Mat image) {

// 亮度降低

Mat dst = new Mat();

Mat black = Mat.zeros(image.size(), image.type());

Core.addWeighted(image, 0.5, black, 0.5, 0, dst);

return dst;

}

public Mat gray(Mat image) {

// 灰度

Mat gray = new Mat();

Imgproc.cvtColor(image, gray, Imgproc.COLOR_BGR2GRAY);

return gray;

}

public Mat sharpen(Mat image) {

// 锐化

Mat dst = new Mat();

float[] sharper = new float[]{0, -1, 0, -1, 5, -1, 0, -1, 0};

Mat operator = new Mat(3, 3, CvType.CV_32FC1);

operator.put(0, 0, sharper);

Imgproc.filter2D(image, dst, -1, operator);

return dst;

}

public Mat blur(Mat image) {

// 高斯模糊

Mat dst = new Mat();

Imgproc.GaussianBlur(image, dst, new Size(15, 15), 0);

return dst;

}

public Mat gradient(Mat image) {

// 梯度

Mat grad_x = new Mat();

Mat grad_y = new Mat();

Mat abs_grad_x = new Mat();

Mat abs_grad_y = new Mat();

Imgproc.Sobel(image, grad_x, CvType.CV_32F, 1, 0);

Imgproc.Sobel(image, grad_y, CvType.CV_32F, 0, 1);

Core.convertScaleAbs(grad_x, abs_grad_x);

Core.convertScaleAbs(grad_y, abs_grad_y);

grad_x.release();

grad_y.release();

Mat gradxy = new Mat();

Core.addWeighted(abs_grad_x, 0.5, abs_grad_y, 0.5, 10, gradxy);

return gradxy;

}

}

可以说简单到哭，此外OpenCV For Java支持各种的图像处理包括形态学操作，二值图像分析、图像特征检测与识别、模板匹配、直方图相关功能等等。常见的机器学习算法与图像分析方法。可以说是功能最强大的图像处理SDK与开发平台之一，本人继续发掘分享！

特别注意

在调用之前，一定要加上这句话

System.loadLibrary(Core.NATIVE_LIBRARY_NAME);

目的是加载OpenCV API相关的DLL支持，没有它是不会正确运行的。以上代码与功能实现是基于JDK8 64位与OpenCV 3.2版本。

for(int col=0; col

index = row*width*dims + col;

b = data[index]&0xff;

g = data[index+1]&0xff;

r = data[index+2]&0xff;

r = 255 - r;

g = 255 - g;

b = 255 - b;

data[index] = (byte)b;

data[index+1] = (byte)g;

data[index+2] = (byte)r;

}

}

image.put(0, 0, data);

return image;

}

public Mat brightness(Mat image) {

// 亮度提升

Mat dst = new Mat();

Mat black = Mat.zeros(image.size(), image.type());

Core.addWeighted(image, 1.2, black, 0.5, 0, dst);

return dst;

}

public Mat darkness(Mat image) {

// 亮度降低

Mat dst = new Mat();

Mat black = Mat.zeros(image.size(), image.type());

Core.addWeighted(image, 0.5, black, 0.5, 0, dst);

return dst;

}

public Mat gray(Mat image) {

// 灰度

Mat gray = new Mat();

Imgproc.cvtColor(image, gray, Imgproc.COLOR_BGR2GRAY);

return gray;

}

public Mat sharpen(Mat image) {

// 锐化

Mat dst = new Mat();

float[] sharper = new float[]{0, -1, 0, -1, 5, -1, 0, -1, 0};

Mat operator = new Mat(3, 3, CvType.CV_32FC1);

operator.put(0, 0, sharper);

Imgproc.filter2D(image, dst, -1, operator);

return dst;

}

public Mat blur(Mat image) {

// 高斯模糊

Mat dst = new Mat();

Imgproc.GaussianBlur(image, dst, new Size(15, 15), 0);

return dst;

}

public Mat gradient(Mat image) {

// 梯度

Mat grad_x = new Mat();

Mat grad_y = new Mat();

Mat abs_grad_x = new Mat();

Mat abs_grad_y = new Mat();

Imgproc.Sobel(image, grad_x, CvType.CV_32F, 1, 0);

Imgproc.Sobel(image, grad_y, CvType.CV_32F, 0, 1);

Core.convertScaleAbs(grad_x, abs_grad_x);

Core.convertScaleAbs(grad_y, abs_grad_y);

grad_x.release();

grad_y.release();

Mat gradxy = new Mat();

Core.addWeighted(abs_grad_x, 0.5, abs_grad_y, 0.5, 10, gradxy);

return gradxy;

}

}

可以说简单到哭，此外OpenCV For Java支持各种的图像处理包括形态学操作，二值图像分析、图像特征检测与识别、模板匹配、直方图相关功能等等。常见的机器学习算法与图像分析方法。可以说是功能最强大的图像处理SDK与开发平台之一，本人继续发掘分享！

特别注意

在调用之前，一定要加上这句话

System.loadLibrary(Core.NATIVE_LIBRARY_NAME);

目的是加载OpenCV API相关的DLL支持，没有它是不会正确运行的。以上代码与功能实现是基于JDK8 64位与OpenCV 3.2版本。

index = row*width*dims + col;

b = data[index]&0xff;

g = data[index+1]&0xff;

r = data[index+2]&0xff;

r = 255 - r;

g = 255 - g;

b = 255 - b;

data[index] = (byte)b;

data[index+1] = (byte)g;

data[index+2] = (byte)r;

}

}

image.put(0, 0, data);

return image;

}

public Mat brightness(Mat image) {

// 亮度提升

Mat dst = new Mat();

Mat black = Mat.zeros(image.size(), image.type());

Core.addWeighted(image, 1.2, black, 0.5, 0, dst);

return dst;

}

public Mat darkness(Mat image) {

// 亮度降低

Mat dst = new Mat();

Mat black = Mat.zeros(image.size(), image.type());

Core.addWeighted(image, 0.5, black, 0.5, 0, dst);

return dst;

}

public Mat gray(Mat image) {

// 灰度

Mat gray = new Mat();

Imgproc.cvtColor(image, gray, Imgproc.COLOR_BGR2GRAY);

return gray;

}

public Mat sharpen(Mat image) {

// 锐化

Mat dst = new Mat();

float[] sharper = new float[]{0, -1, 0, -1, 5, -1, 0, -1, 0};

Mat operator = new Mat(3, 3, CvType.CV_32FC1);

operator.put(0, 0, sharper);

Imgproc.filter2D(image, dst, -1, operator);

return dst;

}

public Mat blur(Mat image) {

// 高斯模糊

Mat dst = new Mat();

Imgproc.GaussianBlur(image, dst, new Size(15, 15), 0);

return dst;

}

public Mat gradient(Mat image) {

// 梯度

Mat grad_x = new Mat();

Mat grad_y = new Mat();

Mat abs_grad_x = new Mat();

Mat abs_grad_y = new Mat();

Imgproc.Sobel(image, grad_x, CvType.CV_32F, 1, 0);

Imgproc.Sobel(image, grad_y, CvType.CV_32F, 0, 1);

Core.convertScaleAbs(grad_x, abs_grad_x);

Core.convertScaleAbs(grad_y, abs_grad_y);

grad_x.release();

grad_y.release();

Mat gradxy = new Mat();

Core.addWeighted(abs_grad_x, 0.5, abs_grad_y, 0.5, 10, gradxy);

return gradxy;

}

}

可以说简单到哭，此外OpenCV For Java支持各种的图像处理包括形态学操作，二值图像分析、图像特征检测与识别、模板匹配、直方图相关功能等等。常见的机器学习算法与图像分析方法。可以说是功能最强大的图像处理SDK与开发平台之一，本人继续发掘分享！

特别注意

在调用之前，一定要加上这句话

System.loadLibrary(Core.NATIVE_LIBRARY_NAME);

目的是加载OpenCV API相关的DLL支持，没有它是不会正确运行的。以上代码与功能实现是基于JDK8 64位与OpenCV 3.2版本。

版权声明：本文内容由网络用户投稿，版权归原作者所有，本站不拥有其著作权，亦不承担相应法律责任。如果您发现本站中有涉嫌抄袭或描述失实的内容，请联系我们jiasou666@gmail.com 处理，核实后本网站将在24小时内删除侵权内容。