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Thresholding enables to achieve image segmentation in the easiest way. Image segmentation means dividing the complete image into a set of pixels in such a way that the pixels in each set have some common characteristics. Image segmentation is highly useful in defining objects and their boundaries.
In this chapter we perform some basic thresholding operations on images.
We use OpenCV function threshold. It can be found under Imgproc package. Its syntax is given below −
Imgproc.threshold(source, destination, thresh , maxval , type);
The parameters are described below −
| 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. |
Apart from these thresholding methods, there are other methods provided by the Imgproc class. They are described briefly −
| 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. |
Example
The following example demonstrates the use of Imgproc class to perform thresholding operations to an image −
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());
}
}
}
Output
When you execute the given code, the following output is seen −
Original Image
On the above original image, some thresholding operations is performed which is shown in the output below −
Thresh Binary
Thresh Binary Invert
Thresh Zero
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