- OpenCV Tutorial
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- Types of Images
- OpenCV - The IMREAD_XXX Flag
- Reading an Image as Grayscale
- OpenCV - Reading Image as BGR
- Image Conversion
- Colored Images to GrayScale
- OpenCV - Colored Image to Binary
- OpenCV - Grayscale to Binary
- Drawing Functions
- OpenCV - Drawing a Circle
- OpenCV - Drawing a Line
- OpenCV - Drawing a Rectangle
- OpenCV - Drawing an Ellipse
- OpenCV - Drawing Polylines
- OpenCV - Drawing Convex Polylines
- OpenCV - Drawing Arrowed Lines
- OpenCV - Adding Text
- Filtering
- OpenCV - Bilateral Filter
- OpenCV - Box Filter
- OpenCV - SQRBox Filter
- OpenCV - Filter2D
- OpenCV - Dilation
- OpenCV - Erosion
- OpenCV - Morphological Operations
- OpenCV - Image Pyramids
- Sobel Derivatives
- OpenCV - Sobel Operator
- OpenCV - Scharr Operator
- Transformation Operations
- OpenCV - Laplacian Transformation
- OpenCV - Distance Transformation
- Camera and Face Detection
- OpenCV - Using Camera
- OpenCV - Face Detection in a Picture
- Face Detection using Camera
- Geometric Transformations
- OpenCV - Affine Translation
- OpenCV - Rotation
- OpenCV - Scaling
- OpenCV - Color Maps
- Miscellaneous Chapters
- OpenCV - Canny Edge Detection
- OpenCV - Hough Line Transform
- OpenCV - Histogram Equalization
- OpenCV Useful Resources
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- OpenCV - Discussion
OpenCV - Affine Translation
You can perform affine translation on an image using the warpAffine() method of the imgproc class. Following is the syntax of this method −
Imgproc.warpAffine(src, dst, tranformMatrix, size);
This method accepts the following parameters −
src − A Mat object representing the source (input image) for this operation.
dst − A Mat object representing the destination (output image) for this operation.
tranformMatrix − A Mat object representing the transformation matrix.
size − A variable of the type integer representing the size of the output image.
Example
The following program demonstrates how to apply affine operation on a given image.
import org.opencv.core.Core; import org.opencv.core.Mat; import org.opencv.core.MatOfPoint2f; import org.opencv.core.Point; import org.opencv.core.Size; import org.opencv.imgcodecs.Imgcodecs; import org.opencv.imgproc.Imgproc; public class AffineTranslation { public static void main(String args[]) { // Loading the OpenCV core library System.loadLibrary( Core.NATIVE_LIBRARY_NAME ); // Reading the Image from the file and storing it in to a Matrix object String file ="E:/OpenCV/chap24/transform_input.jpg"; Mat src = Imgcodecs.imread(file); //Creating an empty matrix to store the result Mat dst = new Mat(); Point p1 = new Point( 0,0 ); Point p2 = new Point( src.cols() - 1, 0 ); Point p3 = new Point( 0, src.rows() - 1 ); Point p4 = new Point( src.cols()*0.0, src.rows()*0.33 ); Point p5 = new Point( src.cols()*0.85, src.rows()*0.25 ); Point p6 = new Point( src.cols()*0.15, src.rows()*0.7 ); MatOfPoint2f ma1 = new MatOfPoint2f(p1,p2,p3); MatOfPoint2f ma2 = new MatOfPoint2f(p4,p5,p6); // Creating the transformation matrix Mat tranformMatrix = Imgproc.getAffineTransform(ma1,ma2); // Creating object of the class Size Size size = new Size(src.cols(), src.cols()); // Applying Wrap Affine Imgproc.warpAffine(src, dst, tranformMatrix, size); // Writing the image Imgcodecs.imwrite("E:/OpenCV/chap24/Affinetranslate.jpg", dst); System.out.println("Image Processed"); } }
Assume that following is the input image transform_input.jpg specified in the above program.
Output
On executing it, you will get the following output −
Image Processed
If you open the specified path, you can observe the output image as follows −
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