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Sobel edge detection algorithm code with C | Sobel edge detection algorithm code with C | ||
void sobel_filtering( ) | void sobel_filtering( ) { | ||
/* Spatial filtering of image data */ | /* Spatial filtering of image data */ | ||
/* Sobel filter (horizontal differentiation */ | /* Sobel filter (horizontal differentiation */ | ||
/* Input: image1[y][x] ---- Outout: image2[y][x] */ | /* Input: image1[y][x] ---- Outout: image2[y][x] */ | ||
/* Definition of Sobel filter in horizontal direction */ | /* Definition of Sobel filter in horizontal direction */ | ||
int maskx[3][3] = {{-1,0,1},{-2,0,2},{-1,0,1}}; | int maskx[3][3] = {{-1,0,1},{-2,0,2},{-1,0,1}}; | ||
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y_size2 = y_size1; | y_size2 = y_size1; | ||
for (y = 0; y < y_size2; y++) { | for (y = 0; y < y_size2; y++) { | ||
for (x = 0; x < x_size2; x++) { | for (x = 0; x < x_size2; x++){ | ||
image2[y][x] = 0; | image2[y][x] = 0; | ||
} | } | ||
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if (pixel_value <= 0)pixel_value=0; | if (pixel_value <= 0)pixel_value=0; | ||
image2[y][x] = (unsigned char)pixel_value; | image2[y][x] = (unsigned char)pixel_value; | ||
} | |||
} | } | ||
} | |||
} | } | ||
} | |||
main( ) | main( ) | ||
{ | { | ||
Revision as of 03:25, 15 February 2012
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Assignment #2
Description of Sobel's Algorithm - This is a great website teachs us how it works, and it also provide some examples, which help us to implement in C code.
Compiler:
gcc -O -lm sobel.c -o sobel
./sobel
Sobel edge detection algorithm code with C (Since the code is very long, I just show key part of algorithm):
int sobel(double threshold) {
unsigned int x, y, i, v, u; // for loop counter
unsigned char R, G, B; // color of R, G, B
double val[MASK_N] = {0.0};
int adjustX, adjustY, xBound, yBound;
double total;
for(y = 0; y != height; ++y) {
for(x = 0; x != width; ++x) {
for(i = 0; i != MASK_N; ++i) {
adjustX = (MASK_X % 2) ? 1 : 0;
adjustY = (MASK_Y % 2) ? 1 : 0;
xBound = MASK_X / 2;
yBound = MASK_Y / 2;
val[i] = 0.0;
for(v = -yBound; v != yBound + adjustY; ++v) {
for (u = -xBound; u != xBound + adjustX; ++u) {
if (x + u >= 0 && x + u < width && y + v >= 0 && y + v < height) {
R = *(image_s + byte_per_pixel * (width * (y+v) + (x+u)) + 2);
G = *(image_s + byte_per_pixel * (width * (y+v) + (x+u)) + 1);
B = *(image_s + byte_per_pixel * (width * (y+v) + (x+u)) + 0);
val[i] += color_to_int(R, G, B) * mask[i][u + xBound][v + yBound];
}
}
}
}
total = 0.0;
for (i = 0; i != MASK_N; ++i) {
total += val[i] * val[i];
}
total = sqrt(total);
if (total - threshold >= 0) {
// black
*(image_t + byte_per_pixel * (width * y + x) + 2) = BLACK;
*(image_t + byte_per_pixel * (width * y + x) + 1) = BLACK;
*(image_t + byte_per_pixel * (width * y + x) + 0) = BLACK;
}
else {
// white
*(image_t + byte_per_pixel * (width * y + x) + 2) = WHITE;
*(image_t + byte_per_pixel * (width * y + x) + 1) = WHITE;
*(image_t + byte_per_pixel * (width * y + x) + 0) = WHITE;
}
}
}
return 0;
}
We use color lena with 24bit bmp file


Profiling Sobel edge detection algorithm
This command will generate a test file:
gcc -lm -pg sobel.c ./a.out gprof a.out > test
test file:
% cumulative self self total 80.80 0.15 0.15 1 145.44 175.53 sobel 16.72 0.18 0.03 4706312 0.00 0.00 color_to_int 0.00 0.18 0.00 1 0.00 0.00 read_bmp 0.00 0.18 0.00 1 0.00 0.00 write_bmp
Assignment #2 (New Algorithm)
Compiler:
gcc -O -lm sobel.c -o sobel
./sobel
Sobel edge detection algorithm code with C
void sobel_filtering( ) {
/* Spatial filtering of image data */
/* Sobel filter (horizontal differentiation */
/* Input: image1[y][x] ---- Outout: image2[y][x] */
/* Definition of Sobel filter in horizontal direction */
int maskx[3][3] = {{-1,0,1},{-2,0,2},{-1,0,1}};
int masky[3][3] = {{1,2,1},{0,0,0},{-1,-2,-1}};
double pixel_value_x, pixel_value_y, pixel_value;
double min, max;
int x, y, i, j; /* Loop variable */
/* Initialization of image2[y][x] */
x_size2 = x_size1;
y_size2 = y_size1;
for (y = 0; y < y_size2; y++) {
for (x = 0; x < x_size2; x++){
image2[y][x] = 0;
}
}
/* Generation of image2 after linear transformtion */
for (y = 1; y < y_size1 - 1; y++) {
for (x = 1; x < x_size1 - 1; x++) {
pixel_value_x = 0.0;
pixel_value_y = 0.0;
for (j = -1; j <= 1; j++) {
for (i = -1; i <= 1; i++) {
pixel_value_x += image1[y+j][x+i] * maskx[j+1][i+1];// do x-convolution
pixel_value_y += image1[y+j][x+i] * masky[j+1][i+1];// do y-convolution
}
pixel_value = (abs(pixel_value_x)+abs(pixel_value_y)); // easier to implement on hardware
if (pixel_value >= 255)pixel_value=255;
if (pixel_value <= 0)pixel_value=0;
image2[y][x] = (unsigned char)pixel_value;
}
}
}
}
main( ) {
load_image_data( ); /* Input of image1 */ sobel_filtering( ); /* Sobel filter is applied to image1 */ save_image_data( ); /* Output of image2 */ return 0;
}