how to view pdf file in asp.net using c# : How to extract images from pdf application software utility azure windows asp.net visual studio cips2ed54-part1054

F.10. CODE LISTINGS FOR CHAPTER 10
519
*
***********************************************/
pixel_grow(input, output, diff,
min_area, max_area,
rows, cols)
long cols, rows;
short **input,
**output,
max_area,
min_area,
diff;
{
char name[80];
int count,
first_call,
i,
ii,
j,
jj,
object_found;
short g_label, target, pop_i, pop_j, sum;
for(i=0; i<rows; i++)
for(j=0; j<cols; j++)
output[i][j] = 0;
g_label
= 2;
object_found = 0;
first_call
= 1;
/*************************************
*
*
Now begin the process of growing
*
regions.
*
**************************************/
for(i=0; i<rows; i++){
if( (i%4) == 0) printf("\n");
printf("-i=%3d label=%3d", i, g_label);
for(j=0; j<cols; j++){
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520
APPENDIX F. SOURCE CODE LISTINGS
target
= input[i][j];
sum
= target;
count
= 0;
/********************************
stack_file_in_use = 0;
stack_empty
= 1;
pointer
= -1;
*******************************/
stackp = NULL;
/**********************************
*
* Search for the first pixel of
* a region. It must not equal
* FORGET_IT, and it must be close
* enough to the target (ave value).
*
***********************************/
if(input[i][j] != FORGET_IT
&&
is_close(input[i][j], target, diff) &&
output[i][j] == 0){
pixel_label_and_check_neighbor(input,
output, &target, &sum,
&count, g_label,
i, j, diff,
&first_call,
rows, cols);
object_found = 1;
} /* ends if is_close */
/*****************************
*
* If the stack is not empty,
* pop the coordinates of
* the pixel off the stack
* and check its 8 neighbors.
*
*******************************/
while(is_not_emptyp(stackp)){
popp(&pop_i, &pop_j);
pixel_label_and_check_neighbor(input,
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F.10. CODE LISTINGS FOR CHAPTER 10
521
output, &target, &sum,
&count, g_label,
pop_i, pop_j,
diff,
&first_call,
rows, cols);
} /* ends while stack_empty == 0 */
if(object_found == 1){
object_found = 0;
/**********************************
*
* The object must be in the
* size constraints given by
* min_area and max_area
*
*********************************/
if(count >= min_area &&
count <= max_area)
++g_label;
/**********************************
*
*
Remove the object from the
*
output. Set all pixels in the
*
object you are removing to
*
FORGET_IT.
*
**********************************/
else{
for(ii=0; ii<rows; ii++){
for(jj=0; jj<cols; jj++){
if(output[ii][jj] == g_label){
output[ii][jj] = 0;
input[ii][jj] = FORGET_IT;
} /* ends if output == g_label */
} /* ends loop over jj */
} /* ends loop over ii */
} /* ends else remove object */
} /* ends if object_found == 1 */
}
/* ends loop over j */
} /* ends loop over i */
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522
APPENDIX F. SOURCE CODE LISTINGS
printf("\nGROW> found %d objects", g_label);
} /* ends pixel_grow */
/********************************************
*
* pixel_label_and_check_neighbors(...
*
* This function labels a pixel with an object
* label and then checks the pixel’s 8
* neighbors. If any of the neigbors are
* set, then they are also labeled.
*
* It also updates the target or ave pixel
* value of the pixels in the region being
* grown.
*
***********************************************/
pixel_label_and_check_neighbor(input_image,
output_image, target,
sum, count,
g_label,
r, e, diff,
first_call,
rows, cols)
int
*count,
e,
*first_call,
r;
long cols, rows;
short **input_image,
**output_image,
g_label,
*sum,
*target,
diff;
{
char response[80];
int already_labeled = 0,
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F.10. CODE LISTINGS FOR CHAPTER 10
523
i, j;
/**printf("\nDEBUG>placn> start rx=%d ey=%d",r,e);**/
if (output_image[r][e] != 0)
already_labeled = 1;
output_image[r][e] = g_label;
*count = *count + 1;
if(*count > 1){
*sum
= *sum + input_image[r][e];
*target = *sum / *count;
}
/***************************************
*
*
Look at the 8 neighors of the
*
point r,e.
*
*
Ensure the points are close enough
*
to the target and do not equal
*
FORGET_IT.
*
*
Ensure the points you are checking
*
are in the image, i.e. not less
*
than zero and not greater than
*
rows-1 or cols-1.
*
***************************************/
for(i=(r-1); i<=(r+1); i++){
for(j=(e-1); j<=(e+1); j++){
if((i>=0)
&& /* ensure point in in image */
(i<=rows-1) &&
(j>=0)
&&
(j<=cols-1)){
if( input_image[i][j] != FORGET_IT
&&
is_close(input_image[i][j],
*target, diff)
&&
output_image[i][j] == 0){
pushp(i, j);
} /* ends if is_close */
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524
APPENDIX F. SOURCE CODE LISTINGS
} /* end if i and j are on the image */
} /* ends loop over i rows
*/
} /* ends loop over j columns
*/
} /* ends pixel_label_and_check_neighbors */
/********************************************
*
* is_close(...
*
* This function tests to see if two pixel
* values are close enough together. It
* uses the delta parameter to make this
* judgement.
*
***********************************************/
is_close(a, b, delta)
short a, b, delta;
{
int
result = 0;
short diff;
diff = a-b;
if(diff < 0) diff = diff*(-1);
if(diff < delta)
result = 1;
return(result);
} /* ends is_close */
/*******************************************
*
*
edge_region(..
*
*
This function segments an image by
*
growing regions inside of edges.
*
The steps are:
*
. detect edges
*
. threshold edge output to a
*
percent value
*
. remove edges from consideration
F.10. CODE LISTINGS FOR CHAPTER 10
525
*
. grow regions
*
*******************************************/
edge_region(the_image, out_image,
edge_type, min_area,
max_area, diff, percent, set_value,
erode, rows, cols, bits_per_pixel)
float
percent;
int
edge_type;
long
bits_per_pixel, cols, rows;
short
diff, erode,
max_area, min_area,
set_value,
**the_image,
**out_image;
{
int
a, b, count, i, j, k,
length, width;
short cutoff;
unsigned long histogram[GRAY_LEVELS+1];
/***************************
*
*
Detect the edges. Do
*
not threshold.
*
****************************/
if(edge_type == 1 ||
edge_type == 2 ||
edge_type == 3)
detect_edges(the_image, out_image,
edge_type, 0, 0,
rows, cols,
bits_per_pixel);
if(edge_type == 4){
quick_edge(the_image, out_image,
0, 0,
rows, cols,
bits_per_pixel);
} /* ends if 4 */
526
APPENDIX F. SOURCE CODE LISTINGS
if(edge_type == 5){
homogeneity(the_image, out_image,
rows, cols,
bits_per_pixel,
0, 0);
} /* ends if 5 */
if(edge_type == 6){
difference_edge(the_image, out_image,
rows, cols,
bits_per_pixel,
0, 0);
} /* ends if 6 */
if(edge_type == 7){
contrast_edge(the_image, out_image,
rows, cols,
bits_per_pixel,
0, 0);
} /* ends if 7 */
if(edge_type == 8){
gaussian_edge(the_image, out_image,
rows, cols,
bits_per_pixel,
3, 0, 0);
} /* ends if 8 */
if(edge_type == 10){
range(the_image, out_image,
rows, cols,
bits_per_pixel,
3, 0, 0);
} /* ends if 10 */
if(edge_type == 11){
variance(the_image, out_image,
rows, cols,
bits_per_pixel,
0, 0);
} /* ends if 11 */
/**write_array_into_tiff_image("f:e1.tif", out_image,
il, ie, ll, le);**/
F.10. CODE LISTINGS FOR CHAPTER 10
527
/* copy out_image to the_image */
for(i=0; i<rows; i++)
for(j=0; j<cols; j++)
the_image[i][j] = out_image[i][j];
/******************************
*
*
Threshold the edge detector
*
output at a given percent.
*
This eliminates the weak
*
edges.
*
*******************************/
zero_histogram(histogram, GRAY_LEVELS+1);
calculate_histogram(the_image, histogram,
rows, cols);
find_cutoff_point(histogram, percent, &cutoff,
rows, cols);
threshold_image_array(the_image, out_image,
GRAY_LEVELS, cutoff,
set_value, rows, cols);
if(erode != 0){
/* copy out_image to the_image */
for(i=0; i<rows; i++)
for(j=0; j<cols; j++)
the_image[i][j] = out_image[i][j];
erode_image_array(the_image, out_image,
set_value, erode,
rows, cols);
} /* ends if erode */
/*******************************
*
*
Set all the edge values to
*
FORGET_IT so the region
*
growing will not use those
*
points.
*
*******************************/
for(i=0; i<rows; i++)
for(j=0; j<cols; j++)
528
APPENDIX F. SOURCE CODE LISTINGS
if(out_image[i][j] == set_value)
out_image[i][j] = FORGET_IT;
for(i=0; i<rows; i++)
for(j=0; j<cols; j++)
the_image[i][j] = out_image[i][j];
pixel_grow(the_image, out_image, diff,
min_area, max_area,
rows, cols);
} /* ends edge_region */
/*******************************************
*
*
gray_shade_region(...
*
*
This function segments an image by
*
growing regions based only on gray
*
shade.
*
*******************************************/
gray_shade_region(the_image, out_image,
diff, min_area, max_area,
rows, cols)
long
cols, rows;
short **the_image,
**out_image,
diff, min_area, max_area;
{
int
a, b, big_count, count, i, j, k, l,
not_finished, length, width;
printf("\nDEBUG> GSR> before calling pixel grow");
pixel_grow(the_image, out_image, diff,
min_area, max_area,
rows, cols);
printf("\nDEBUG> GSR> after calling pixel grow");
} /* ends gray_shade_region */
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