📜  Java DIP-Prewitt运算符

📅  最后修改于: 2020-12-14 05:41:38             🧑  作者: Mango


Prewitt运算符用于图像中的边缘检测。它检测两种类型的边缘:垂直边缘和水平边缘。

我们使用OpenCV函数filter2D将Prewitt运算符应用于图像。可以在Imgproc软件包下找到。其语法如下-

filter2D(src, dst, depth , kernel, anchor, delta, BORDER_DEFAULT );

函数参数描述如下-

Sr.No. Argument & Description
1

src

It is source image.

2

dst

It is destination image.

3

depth

It is the depth of dst. A negative value (such as -1) indicates that the depth is the same as the source.

4

kernel

It is the kernel to be scanned through the image.

5

anchor

It is the position of the anchor relative to its kernel. The location Point (-1, -1) indicates the center by default.

6

delta

It is a value to be added to each pixel during the convolution. By default it is 0.

7

BORDER_DEFAULT

We let this value by default.

除了filter2D方法之外,Imgproc类还提供其他方法。他们简要描述-

Sr.No. Method & Description
1

cvtColor(Mat src, Mat dst, int code, int dstCn)

It converts an image from one color space to another.

2

dilate(Mat src, Mat dst, Mat kernel)

It dilates an image by using a specific structuring element.

3

equalizeHist(Mat src, Mat dst)

It equalizes the histogram of a grayscale image.

4

filter2D(Mat src, Mat dst, int depth, Mat kernel, Point anchor, double delta)

It convolves an image with the kernel.

5

GaussianBlur(Mat src, Mat dst, Size ksize, double sigmaX)

It blurs an image using a Gaussian filter.

6

integral(Mat src, Mat sum)

It calculates the integral of an image.

下面的示例演示如何使用Imgproc类将Prewitt运算符应用于灰度图像。

import org.opencv.core.Core;
import org.opencv.core.CvType;
import org.opencv.core.Mat;

import org.opencv.highgui.Highgui;
import org.opencv.imgproc.Imgproc;

public class convolution {
   public static void main( String[] args ) {
      try {
         int kernelSize = 9;
         System.loadLibrary( Core.NATIVE_LIBRARY_NAME );
         
         Mat source = Highgui.imread("grayscale.jpg", Highgui.CV_LOAD_IMAGE_GRAYSCALE);
         Mat destination = new Mat(source.rows(),source.cols(),source.type());
         
         Mat kernel = new Mat(kernelSize,kernelSize, CvType.CV_32F) {
            {
               put(0,0,-1);
               put(0,1,0);
               put(0,2,1);

               put(1,0-1);
               put(1,1,0);
               put(1,2,1);

               put(2,0,-1);
               put(2,1,0);
               put(2,2,1);
            }
         };     
         
         Imgproc.filter2D(source, destination, -1, kernel);
         Highgui.imwrite("output.jpg", destination);
         
      } catch (Exception e) {
         System.out.println("Error: " + e.getMessage());
      }
   }
}

输出

当您执行给定的代码时,将看到以下输出-

原始图片

应用Prewitt运算符教程

原始图像与垂直边缘的Prewitt运算符卷积,如下所示-

垂直方向

-1 0 1
-1 0 1
-1 0 1

卷积图像(垂直方向)

应用Prewitt运算符教程

该原始图像还已经与水平边缘的Prewitt运算符进行了卷积运算,如下所示:

水平方向

-1 -1 -1
0 0 0
1 1 1

卷积图像(水平方向)

应用Prewitt运算符教程