# Example Image Derivative

From BoofCV

Jump to navigationJump to searchExample of how to compute different image derivatives. The gradient (1st order derivative) is probably the important image derivative and is used as a first step when extracting many types of image features. The code below shows how gradient, Hessian (2nd order), and arbitrary image derivatives can be computed.

Example Code:

Concepts:

- Image Derivative
- Gradient
- Hessian

# Example Code

```
/**
* Example showing how to compute different image derivatives using built in functions.
*
* @author Peter Abeles
*/
public class ExampleImageDerivative {
public static void main( String[] args ) {
BufferedImage input = UtilImageIO.loadImage(UtilIO.pathExample("simple_objects.jpg"));
// We will use floating point images here, but GrayU8 with GrayS16 for derivatives also works
GrayF32 grey = new GrayF32(input.getWidth(), input.getHeight());
ConvertBufferedImage.convertFrom(input, grey);
// First order derivative, also known as the gradient
GrayF32 derivX = new GrayF32(grey.width, grey.height);
GrayF32 derivY = new GrayF32(grey.width, grey.height);
GImageDerivativeOps.gradient(DerivativeType.SOBEL, grey, derivX, derivY, BorderType.EXTENDED);
// Second order derivative, also known as the Hessian
GrayF32 derivXX = new GrayF32(grey.width, grey.height);
GrayF32 derivXY = new GrayF32(grey.width, grey.height);
GrayF32 derivYY = new GrayF32(grey.width, grey.height);
GImageDerivativeOps.hessian(DerivativeType.SOBEL, derivX, derivY, derivXX, derivXY, derivYY, BorderType.EXTENDED);
// There's also a built in function for computing arbitrary derivatives
AnyImageDerivative<GrayF32, GrayF32> derivative =
GImageDerivativeOps.createAnyDerivatives(DerivativeType.SOBEL, GrayF32.class, GrayF32.class);
// the boolean sequence indicates if its an X or Y derivative
derivative.setInput(grey);
GrayF32 derivXYX = derivative.getDerivative(true, false, true);
// Visualize the results
ListDisplayPanel gui = new ListDisplayPanel();
gui.addImage(ConvertBufferedImage.convertTo(grey, null), "Input Grey");
gui.addImage(VisualizeImageData.colorizeSign(derivX, null, -1), "Sobel X");
gui.addImage(VisualizeImageData.colorizeSign(derivY, null, -1), "Sobel Y");
// Use colors to show X and Y derivatives in one image. Looks pretty.
gui.addImage(VisualizeImageData.colorizeGradient(derivX, derivY, -1, null), "Sobel X and Y");
gui.addImage(VisualizeImageData.colorizeSign(derivXX, null, -1), "Sobel XX");
gui.addImage(VisualizeImageData.colorizeSign(derivXY, null, -1), "Sobel XY");
gui.addImage(VisualizeImageData.colorizeSign(derivYY, null, -1), "Sobel YY");
gui.addImage(VisualizeImageData.colorizeSign(derivXYX, null, -1), "Sobel XYX");
ShowImages.showWindow(gui, "Image Derivatives", true);
}
}
```