timoreo/quirc
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity

Replace existing threshold function with Otsu threshold algorithm

Browse source
This commit is contained in:
Claudio Felber 2019-04-30 13:02:11 +02:00
parent 307473dbca
commit 97ffaabfb5
1 changed files with 56 additions and 60 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

116
lib/identify.c
View file

@ -174,60 +174,55 @@ static void flood_fill_seed(struct quirc *q, int x, int y, int from, int to,
* Adaptive thresholding
*/
#define THRESHOLD_S_MIN 1
#define THRESHOLD_S_DEN 8
#define THRESHOLD_T 5
static void threshold(struct quirc *q)
uint8_t otsu(struct quirc *q)
{
int x, y;
int avg_w = 0;
int avg_u = 0;
int threshold_s = q->w / THRESHOLD_S_DEN;
quirc_pixel_t *row = q->pixels;
int numPixels = q->w * q->h;
/*
* Ensure a sane, non-zero value for threshold_s.
*
* threshold_s can be zero if the image width is small. We need to avoid
* SIGFPE as it will be used as divisor.
*/
if (threshold_s < THRESHOLD_S_MIN)
threshold_s = THRESHOLD_S_MIN;
// Calculate histogram
const int HISTOGRAM_SIZE = 256;
unsigned int histogram[HISTOGRAM_SIZE];
memset(histogram, 0, (HISTOGRAM_SIZE) * sizeof(unsigned int));
uint8_t* ptr = q->image;
int length = numPixels;
while (length--) {
uint8_t value = *ptr++;
histogram[value]++;
}
for (y = 0; y < q->h; y++) {
memset(q->row_average, 0, q->w * sizeof(int));
// Calculate weighted sum of histogram values
int sum = 0;
for (int i = 0; i < HISTOGRAM_SIZE; ++i) {
sum += i * histogram[i];
}
for (x = 0; x < q->w; x++) {
int w, u;
// Compute threshold
int sumB = 0;
int q1 = 0;
double max = 0;
uint8_t threshold = 0;
for (int i = 0; i < HISTOGRAM_SIZE; ++i) {
// Weighted background
q1 += histogram[i];
if (q1 == 0)
continue;
if (y & 1) {
w = x;
u = q->w - 1 - x;
} else {
w = q->w - 1 - x;
u = x;
}
// Weighted foreground
const int q2 = numPixels - q1;
if (q2 == 0)
break;
avg_w = (avg_w * (threshold_s - 1)) /
threshold_s + row[w];
avg_u = (avg_u * (threshold_s - 1)) /
threshold_s + row[u];
sumB += i * histogram[i];
const double m1 = (double)sumB / q1;
const double m2 = ((double)sum - sumB) / q2;
const double m1m2 = m1 - m2;
const double variance = m1m2 * m1m2 * q1 * q2;
if (variance > max) {
threshold = i;
max = variance;
}
}
q->row_average[w] += avg_w;
q->row_average[u] += avg_u;
}
for (x = 0; x < q->w; x++) {
if (row[x] < q->row_average[x] *
(100 - THRESHOLD_T) / (200 * threshold_s))
row[x] = QUIRC_PIXEL_BLACK;
else
row[x] = QUIRC_PIXEL_WHITE;
}
row += q->w;
}
return threshold;
}
static void area_count(void *user_data, int y, int left, int right)
@ -1074,18 +1069,19 @@ static void test_grouping(struct quirc *q, int i)
test_neighbours(q, i, &hlist, &vlist);
}
static void pixels_setup(struct quirc *q)
static void pixels_setup(struct quirc *q, uint8_t threshold)
{
if (sizeof(*q->image) == sizeof(*q->pixels)) {
q->pixels = (quirc_pixel_t *)q->image;
} else {
int x, y;
for (y = 0; y < q->h; y++) {
for (x = 0; x < q->w; x++) {
q->pixels[y * q->w + x] = q->image[y * q->w + x];
}
}
}
if (sizeof(*q->image) == sizeof(*q->pixels)) {
q->pixels = (quirc_pixel_t *)q->image;
}
uint8_t* source = q->image;
quirc_pixel_t* dest = q->pixels;
int length = q->w * q->h;
while (length--) {
uint8_t value = *source++;
*dest++ = (value < threshold) ? QUIRC_PIXEL_BLACK : QUIRC_PIXEL_WHITE;
}
}
uint8_t *quirc_begin(struct quirc *q, int *w, int *h)
@ -1106,8 +1102,8 @@ void quirc_end(struct quirc *q)
{
int i;
pixels_setup(q);
threshold(q);
uint8_t threshold = otsu(q);
pixels_setup(q, threshold);
for (i = 0; i < q->h; i++)
finder_scan(q, i);