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F.9. CODE LISTINGS FOR CHAPTER 9
489
*
15 August 1998 - modified to work on
*
images at once.
*
************************************************/
#include "cips.h"
struct stacks{
short
x;
short
y;
struct stacks *next;
};
struct stacks *stack;
/**************************************************
*
*
threshold_image_array(...
*
*
This function thresholds an input image array
*
and produces a binary output image array.
*
If the pixel in the input array is between
*
the hi and low values, then it is set to value.
*
Otherwise, it is set to 0.
*
***************************************************/
threshold_image_array(in_image, out_image,
hi, low, value,
rows, cols)
short hi, low, **in_image,
**out_image, value;
int
rows, cols;
{
int
i, j;
unsigned long counter = 0L;
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490
APPENDIX F. SOURCE CODE LISTINGS
for(i=0; i<rows; i++){
for(j=0; j<cols; j++){
if(in_image[i][j] >= low &&
in_image[i][j] <= hi){
out_image[i][j] = value;
counter++;
}
else
out_image[i][j] = 0;
} /* ends loop over j */
} /* ends loop over i */
printf("\n\tTIA> set %ld points", counter);
} /* ends threshold_image_array */
/**********************************************
*
* grow(...
*
* This function is an object detector.
* Its input is an binary image array
* containing 0’s and value’s.
* It searches through the image and connects
* the adjacent values.
*
***********************************************/
grow(binary, value, rows, cols)
short **binary,
value;
{
int
first_call,
i,
j,
object_found;
short g_label,
pop_i,
pop_j;
/*************************************
*
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F.9. CODE LISTINGS FOR CHAPTER 9
491
*
Now begin the process of growing
*
regions.
*
**************************************/
g_label
= 2;
object_found = 0;
first_call
= 1;
for(i=0; i<rows; i++){
for(j=0; j<cols; j++){
stack = NULL;
/**********************************
*
* Search for the first pixel of
* a region.
*
***********************************/
if(binary[i][j] == value){
/*printf("\nGROW> Hit value at %d %d number %d",i,j,g_label);*/
label_and_check_neighbor(
binary,
g_label,
i, j, value,
&first_call,
rows, cols);
object_found = 1;
} /* ends if binary[i]j] == value */
/*****************************
*
* If the stack is not empty,
* pop the coordinates of
* the pixel off the stack
* and check its 8 neighbors.
*
*******************************/
while(is_not_empty(stack)){
pop(&pop_i, &pop_j);
label_and_check_neighbor(
binary,
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492
APPENDIX F. SOURCE CODE LISTINGS
g_label,
pop_i,
pop_j, value,
&first_call,
rows, cols);
} /* ends while stack_empty == 0 */
if(object_found == 1){
object_found = 0;
++g_label;
} /* ends if object_found == 1 */
}
/* ends loop over j */
} /* ends loop over i */
printf("\nGROW> found %d objects", g_label);
} /* ends grow */
/********************************************
*
* 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.
*
***********************************************/
label_and_check_neighbor(binary_image,
g_label,
r, e, value,
first_call,
rows, cols)
int
cols,
e,
*first_call,
r,
rows;
short **binary_image,
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F.9. CODE LISTINGS FOR CHAPTER 9
493
g_label,
value;
{
char rr[80];
int already_labeled = 0,
i, j;
struct stacks *temp;
if (binary_image[r][e] == g_label)
already_labeled = 1;
binary_image[r][e] = g_label;
/***************************************
*
*
Look at the 8 neighors of the
*
point r,e.
*
*
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++){
/********************************
*
*
Ensure i and j are not
*
outside the boundary of the
*
image.
*
*********************************/
if((i>=0)
&&
(i<=rows-1) &&
(j>=0)
&&
(j<=cols-1)){
if(binary_image[i][j] == value){
push(i, j);
} /* end of if binary_image == value */
} /* end if i and j are on the image */
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494
APPENDIX F. SOURCE CODE LISTINGS
} /* ends loop over i rows
*/
} /* ends loop over j columns
*/
} /* ends label_and_check_neighbors */
/**************************************************
*
*
manual_threshold_segmentation(...
*
*
This function segments an image using thresholding
*
given the hi and low values of the threshold
*
by the calling routine. It reads in an image
*
and writes the result to the output image.
*
*
If the segment parameter is 0, you only
*
threshold the array - you do not segment.
*
***************************************************/
manual_threshold_segmentation(the_image, out_image,
hi, low, value, segment,
rows, cols)
int
rows, cols, segment;
short hi, low, **the_image,
**out_image, value;
{
threshold_image_array(the_image, out_image,
hi, low, value, rows, cols);
if(segment == 1)
grow(out_image, value, rows, cols);
} /* ends manual_threshold_segmentation */
F.9. CODE LISTINGS FOR CHAPTER 9
495
/************************************************
*
*
peak_threshold_segmentation(...
*
*
This function segments an image using
*
thresholding. It uses the histogram peaks
*
to find the hi and low values of the
*
threshold.
*
*
If the segment parameter is 0, you only
*
threshold the array - you do not segment.
*
*************************************************/
peak_threshold_segmentation(the_image, out_image,
value, segment,
rows, cols)
int
rows, cols, segment;
short **the_image, **out_image, value;
{
int
peak1, peak2;
short
hi, low;
unsigned long histogram[GRAY_LEVELS+1];
zero_histogram(histogram, GRAY_LEVELS+1);
calculate_histogram(the_image, histogram,
rows, cols);
smooth_histogram(histogram, GRAY_LEVELS+1);
find_peaks(histogram, &peak1, &peak2);
peaks_high_low(histogram, peak1, peak2,
&hi, &low);
threshold_image_array(the_image,
out_image,
hi, low, value,
rows, cols);
if(segment == 1)
grow(out_image, value, rows, cols);
} /* ends peak_threshold_segmentation */
/********************************************
496
APPENDIX F. SOURCE CODE LISTINGS
*
*
find_peaks(...
*
*
This function looks through the histogram
*
array and finds the two highest peaks.
*
The peaks must be separated, cannot be
*
next to each other, by a spacing defined
*
in cips.h.
*
*
The peaks array holds the peak value
*
in the first place and its location in
*
the second place.
*
*********************************************/
find_peaks(histogram, peak1, peak2)
unsigned long histogram[];
int *peak1, *peak2;
{
int distance[PEAKS], peaks[PEAKS][2];
int i, j=0, max=0, max_place=0;
for(i=0; i<PEAKS; i++){
distance[i] = 0;
peaks[i][0] = -1;
peaks[i][1] = -1;
}
for(i=0; i<=GRAY_LEVELS; i++){
max
= histogram[i];
max_place = i;
insert_into_peaks(peaks, max, max_place);
} /* ends loop over i */
for(i=1; i<PEAKS; i++){
distance[i] = peaks[0][1] - peaks[i][1];
if(distance[i] < 0)
distance[i] = distance[i]*(-1);
}
*peak1 = peaks[0][1];
for(i=PEAKS-1; i>0; i--)
if(distance[i] > PEAK_SPACE) *peak2 = peaks[i][1];
} /* ends find_peaks */
F.9. CODE LISTINGS FOR CHAPTER 9
497
/********************************************
*
*
insert_into_peaks(...
*
*
This function takes a value and its
*
place in the histogram and inserts them
*
into a peaks array. This helps us rank
*
the the peaks in the histogram.
*
*
The objective is to build a list of
*
histogram peaks and thier locations.
*
*
The peaks array holds the peak value
*
in the first place and its location in
*
the second place.
*
*********************************************/
insert_into_peaks(peaks, max, max_place)
int max, max_place, peaks[PEAKS][2];
{
int i, j;
/* first case */
if(max > peaks[0][0]){
for(i=PEAKS-1; i>0; i--){
peaks[i][0] = peaks[i-1][0];
peaks[i][1] = peaks[i-1][1];
}
peaks[0][0] = max;
peaks[0][1] = max_place;
} /* ends if */
/* middle cases */
for(j=0; j<PEAKS-3; j++){
if(max < peaks[j][0] && max > peaks[j+1][0]){
for(i=PEAKS-1; i>j+1; i--){
peaks[i][0] = peaks[i-1][0];
peaks[i][1] = peaks[i-1][1];
}
498
APPENDIX F. SOURCE CODE LISTINGS
peaks[j+1][0] = max;
peaks[j+1][1] = max_place;
} /* ends if */
} /* ends loop over j */
/* last case */
if(max < peaks[PEAKS-2][0] &&
max > peaks[PEAKS-1][0]){
peaks[PEAKS-1][0] = max;
peaks[PEAKS-1][1] = max_place;
} /* ends if */
} /* ends insert_into_peaks */
/********************************************
*
*
peaks_high_low(...
*
*
This function uses the histogram array
*
and the peaks to find the best high and
*
low threshold values for the threshold
*
function. You want the hi and low values
*
so that you will threshold the image around
*
the smaller of the two "humps" in the
*
histogram. This is because the smaller
*
hump represents the objects while the
*
larger hump represents the background.
*
*********************************************/
peaks_high_low(histogram, peak1, peak2, hi, low)
int peak1, peak2;
short *hi, *low;
unsigned long histogram[];
{
int i, mid_point;
unsigned long sum1 = 0, sum2 = 0;
if(peak1 > peak2)
mid_point = ((peak1 - peak2)/2) + peak2;
if(peak1 < peak2)
mid_point = ((peak2 - peak1)/2) + peak1;
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