📅  最后修改于: 2020-12-14 05:38:55             🧑  作者: Mango
阈值使您能够以最简单的方式实现图像分割。图像分割是指将整个图像分成一组像素,以使每组中的像素具有一些共同的特征。图像分割在定义对象及其边界时非常有用。
在本章中,我们对图像执行一些基本的阈值操作。
我们使用OpenCV函数阈值。可以在Imgproc软件包下找到。其语法如下-
Imgproc.threshold(source, destination, thresh , maxval , type);
参数说明如下-
Sr.No. | Parameter & Description |
---|---|
1 |
source It is source image. |
2 |
destination It is destination image. |
3 |
thresh It is threshold value. |
4 |
maxval It is the maximum value to be used with the THRESH_BINARY and THRESH_BINARY_INV threshold types. |
5 |
type The possible types are THRESH_BINARY, THRESH_BINARY_INV, THRESH_TRUNC, and THRESH_TOZERO. |
除了这些阈值方法外,Imgproc类还提供了其他方法。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 ddepth, 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. |
以下示例演示了使用Imgproc类对图像执行阈值操作-
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 main {
public static void main( String[] args ) {
try{
System.loadLibrary( Core.NATIVE_LIBRARY_NAME );
Mat source = Highgui.imread("digital_image_processing.jpg", Highgui.CV_LOAD_IMAGE_COLOR);
Mat destination = new Mat(source.rows(),source.cols(),source.type());
destination = source;
Imgproc.threshold(source,destination,127,255,Imgproc.THRESH_TOZERO);
Highgui.imwrite("ThreshZero.jpg", destination);
} catch (Exception e) {
System.out.println("error: " + e.getMessage());
}
}
}
当您执行给定的代码时,将看到以下输出-
在上面的原始图像上,执行了一些阈值操作,如下面的输出所示-