ArrayFire: image_processing/adaptive_thresholding.cpp (original) (raw)

#include

#include

#include

using namespace af;

using std::abs;

typedef enum { MEAN = 0, MEDIAN, MINMAX_AVG } LocalThresholdType;

array threshold(const array &in, float thresholdValue) {

int channels = in.dims(2);

if (channels > 1) ret_val = colorSpace(in, AF_GRAY, AF_RGB);

ret_val =

(ret_val < thresholdValue) * 0.0f + 255.0f * (ret_val > thresholdValue);

return ret_val;

}

array adaptiveThreshold(const array &in, LocalThresholdType kind,

int window_size, int constnt) {

int wr = window_size;

if (kind == MEAN) {

ret_val = (diff < constnt) * 0.f + 255.f * (diff > constnt);

} else if (kind == MEDIAN) {

array diff = medf - ret_val;

ret_val = (diff < constnt) * 0.f + 255.f * (diff > constnt);

} else if (kind == MINMAX_AVG) {

ret_val = (diff < constnt) * 0.f + 255.f * (diff > constnt);

}

ret_val = 255.f - ret_val;

return ret_val;

}

array iterativeThreshold(const array &in) {

float T = mean(ret_val);

bool isContinue = true;

while (isContinue) {

array region1 = (ret_val > T) * ret_val;

array region2 = (ret_val <= T) * ret_val;

float r1_avg = mean(region1);

float r2_avg = mean(region2);

float tempT = (r1_avg + r2_avg) / 2.0f;

if (abs(tempT - T) < 0.01f) { break; }

T = tempT;

}

return threshold(ret_val, T);

}

int main(int argc, char **argv) {

try {

int device = argc > 1 ? atoi(argv[1]) : 0;

loadImage(ASSETS_DIR "/examples/images/sudoku.jpg", true);

array mnt = adaptiveThreshold(sudoku, MEAN, 37, 10);

array mdt = adaptiveThreshold(sudoku, MEDIAN, 7, 4);

array mmt = adaptiveThreshold(sudoku, MINMAX_AVG, 11, 4);

array itt = 255.0f - iterativeThreshold(sudoku);

af::Window wnd("Adaptive Thresholding Algorithms");

printf("Press ESC while the window is in focus to exit\n");

while (!wnd.close()) {

wnd.grid(2, 3);

wnd(0, 0).image(sudoku / 255, "Input");

wnd(1, 0).image(mnt, "Adap. Threshold(Mean)");

wnd(0, 1).image(mdt, "Adap. Threshold(Median)");

wnd(1, 1).image(mmt, "Adap. Threshold(Avg. Min,Max)");

wnd(0, 2).image(itt, "Iterative Threshold");

wnd.show();

}

fprintf(stderr, "%s\n", e.what());

throw;

}

return 0;

}

Window object to render af::arrays.

A multi dimensional data container.

dim4 dims() const

Get dimensions of the array.

array copy() const

Perform deep copy of the array.

An ArrayFire exception class.

virtual const char * what() const

Returns an error message for the exception in a string format.

AFAPI array abs(const array &in)

C++ Interface to calculate the absolute value.

array constant(T val, const dim4 &dims, const dtype ty=(af_dtype) dtype_traits< T >::ctype)

C++ Interface to generate an array with elements set to a specified value.

AFAPI void setDevice(const int device)

Sets the current device.

AFAPI array colorSpace(const array &image, const CSpace to, const CSpace from)

C++ Interface wrapper for colorspace conversion.

AFAPI array maxfilt(const array &in, const dim_t wind_length=3, const dim_t wind_width=3, const borderType edge_pad=AF_PAD_ZERO)

C++ Interface for maximum filter.

AFAPI array medfilt(const array &in, const dim_t wind_length=3, const dim_t wind_width=3, const borderType edge_pad=AF_PAD_ZERO)

C++ Interface for median filter.

AFAPI array minfilt(const array &in, const dim_t wind_length=3, const dim_t wind_width=3, const borderType edge_pad=AF_PAD_ZERO)

C++ Interface for minimum filter.

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.

AFAPI array mean(const array &in, const dim_t dim=-1)

C++ Interface for mean.