A high-performance general-purpose compute library
* Copyright (c) 2014, ArrayFire
* All rights reserved.
* This file is distributed under 3-clause BSD license.
* The complete license agreement can be obtained at:
* http://arrayfire.com/licenses/BSD-3-Clause
#include <arrayfire.h>
#include <stdio.h>
#include <af/util.h>
#include <cstdlib>
using namespace af;
void prewitt(array &mag, array &dir, const array &in) {
static float h1[] = {1, 1, 1};
static float h2[] = {-1, 0, 1};
static array colf(3, 1, h1);
static array rowf(3, 1, h2);
// Find the gradients
array Gy = convolve(rowf, colf, in);
array Gx = convolve(colf, rowf, in);
// Find magnitude and direction
mag = hypot(Gx, Gy);
dir = atan2(Gy, Gx);
void sobelFilter(array &mag, array &dir, const array &in) {
array Gx, Gy;
sobel(Gx, Gy, in, 3);
// Find magnitude and direction
mag = hypot(Gx, Gy);
dir = atan2(Gy, Gx);
array normalize(const array &in) {
float mx = max<float>(in);
float mn = min<float>(in);
return (in - mn) / (mx - mn);
array edge(const array &in, int method = 0) {
int w = 5;
if (in.dims(0) < 512) w = 3;
if (in.dims(0) > 2048) w = 7;
int h = 5;
if (in.dims(0) < 512) h = 3;
if (in.dims(0) > 2048) h = 7;
array ker = gaussianKernel(w, h);
array smooth = convolve(in, ker);
array mag, dir;
switch (method) {
case 1: prewitt(mag, dir, smooth); break;
case 2: sobelFilter(mag, dir, smooth); break;
case 3:
mag = canny(in, AF_CANNY_THRESHOLD_AUTO_OTSU, 0.18, 0.54).as(f32);
default: throw af::exception("Unsupported type");
return normalize(mag);
void edge() {
af::Window myWindow("Edge Dectectors");
af::Window myWindow2(512, 512, "Histogram");
array in = loadImage(ASSETS_DIR "/examples/images/trees_ctm.jpg", false);
array prewitt = edge(in, 1);
array sobelFilter = edge(in, 2);
array hst = histogram(in, 256, 0, 255);
array cny = edge(in, 3);
myWindow2.setAxesTitles("Bins", "Frequency");
while (!myWindow.close() && !myWindow2.close()) {
/* show input, prewitt and sobel edge detectors in a grid */
myWindow.grid(2, 2);
myWindow(0, 0).image(in / 255, "Input Image");
myWindow(0, 1).image(prewitt, "Prewitt");
myWindow(1, 0).image(sobelFilter, "Sobel");
myWindow(1, 1).image(cny, "Canny");
/* show histogram on input in separate window */
myWindow2.hist(hst, 0, 255);
int main(int argc, char *argv[]) {
int device = argc > 1 ? atoi(argv[1]) : 0;
try {
printf("** ArrayFire Edge Detection Demo **\n");
} catch (af::exception &e) {
fprintf(stderr, "%s\n", e.what());
return 0;
Window object to render af::arrays.
Definition: graphics.h:37
A multi dimensional data container.
Definition: array.h:37
dim4 dims() const
Get dimensions of the array.
const array as(dtype type) const
Casts the array into another data type.
An ArrayFire exception class.
Definition: exception.h:22
virtual const char * what() const
Returns an error message for the exception in a string format.
Definition: exception.h:46
@ f32
32-bit floating point values
Definition: defines.h:211
Determine canny algorithm thresholds using Otsu algorithm.
Definition: defines.h:485
AFAPI void info()
AFAPI void setDevice(const int device)
Sets the current device.
AFAPI array canny(const array &in, const cannyThreshold thresholdType, const float lowThresholdRatio, const float highThresholdRatio, const unsigned sobelWindow=3, const bool isFast=false)
C++ Interface for canny edge detector.
AFAPI array gaussianKernel(const int rows, const int cols, const double sig_r=0, const double sig_c=0)
C++ Interface for generating gausian kernels.
AFAPI array histogram(const array &in, const unsigned nbins, const double minval, const double maxval)
C++ Interface for histogram.
AFAPI array loadImage(const char *filename, const bool is_color=false)
C++ Interface for loading an image.
AFAPI array convolve(const array &signal, const array &filter, const convMode mode=AF_CONV_DEFAULT, const convDomain domain=AF_CONV_AUTO)
C++ Interface for convolution any(one through three) dimensional signals.
Definition: algorithm.h:15