Prerequisites:
- Image Processing in Java – Read and Write
- Image Processing In Java – Get and Set Pixels
- Image Processing in Java – Colored Image to Grayscale Image Conversion
- Image Processing in Java – Colored Image to Negative Image Conversion
- Image Processing in Java – Colored to Red Green Blue Image Conversion
- Image Processing in Java – Colored Image to Sepia Image Conversion
- Image Processing in Java – Creating a Random Pixel Image
- Image Processing in Java – Creating a Mirror Image
Face Detection using OpenCV
In the Introductory Set on Image Processing, BufferedImage class of Java was used for processing images the applications of BufferedImage class are limited to some operations only, i.e, we can modify the R, G, B values of the given input image and produce the modified image. For complex image processing such as face/object detection, the OpenCV library is used which we will use in this article.
At first, we need to set up OpenCV for Java, we recommend using eclipse for the same since it is easy to use and set up. Now let us understand some of the methods required for face detection.
- CascadeClassifier(): This class is used to load the trained cascaded set of faces which we will be using to detect faces for any input image.
- Imcodecs.imread()/Imcodecs.imwrite() : These methods are used to read and write images as Mat objects which are rendered by OpenCV.
- Imgproc.rectangle() : Used to generate rectangle box outlining faces detected, it takes four arguments – input_image, top_left_point, bottom_right_point, color_of_border.
Implementation:
Note: The front face cascade file can be downloaded from a local git repository.
The input image is as follows:
Example:
Java
// Java Program to Demonstrate Face Detection// Using OpenCV Library // Importing package modulepackage ocv; // Importing required classesimport org.opencv.core.Core;import org.opencv.core.Mat;import org.opencv.core.MatOfRect;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;import org.opencv.objdetect.CascadeClassifier; // Main class// FaceDetectorpublic class GFG { // Main driver method public static void main(String[] args) { // For proper execution of native libraries // Core.NATIVE_LIBRARY_NAME must be loaded before // calling any of the opencv methods System.loadLibrary(Core.NATIVE_LIBRARY_NAME); // Face detector creation by loading source cascade // xml file using CascadeClassifier and must be // placed in same directory of the source java file // File is available here on git as mentioned above // prior to code CascadeClassifier faceDetector = new CascadeClassifier(); faceDetector.load( "haarcascade_frontalface_alt.xml"); // Reading the input image Mat image = Imgcodecs.imread("E:\\input.jpg"); // Detecting faces MatOfRect faceDetections = new MatOfRect(); faceDetector.detectMultiScale(image, faceDetections); // Creating a rectangular box which represents for // faces detected for (Rect rect : faceDetections.toArray()) { Imgproc.rectangle( image, new Point(rect.x, rect.y), new Point(rect.x + rect.width, rect.y + rect.height), new Scalar(0, 255, 0)); } // Saving the output image String filename = "Ouput.jpg"; Imgcodecs.imwrite("E:\\" + filename, image); // Display message for successful execution of // program System.out.print("Face Detected"); }} |
Output:
Face Detected
The output of the program is shown below my pic before and after face detection
Output Explanation:
- It loads the native OpenCV library to use Java API. An instance of CascadeClassifier is created, passing it the name of the file from which the classifier is loaded.
- Next, the detectMultiScale method is used on the classifier passing it the given image and MatOfRect object.
- MatOfRect is responsible to do face detections after processing.
- The process is iterated for doing all the face detections and marking the image with rectangles and at the end, the image is saved as an “output.png” file.
This article is contributed by Pratik Agarwal. If you like Lazyroar and would like to contribute, you can also write an article using write.geeksforgeeks.org or mail your article to review-team@geeksforgeeks.org. See your article appearing on the Lazyroar main page and help other Geeks. Please write comments if you find anything incorrect, or you want to share more information about the topic discussed above.
