I am new to computer vision, but I need to make a small function in C ++ that will detect a sheet of white paper, even if something is printed on it, and get 4 coordinates of the edges, which I really need so I can use these coordinates and cut another jpg file and use the sliced image as opengl textures. I do not know how to identify paper. Try to find computer vision and find that I need a threshold image, do the marking, then use edge detection or harris detection, but did not find any tutorial. Can someone help me with this or show me some kind of tutorial that can help me?
Just find this:
int arDetectMarker( ARUint8 *dataPtr, int thresh,
ARMarkerInfo **marker_info, int *marker_num )
{
ARInt16 *limage;
int label_num;
int *area, *clip, *label_ref;
double *pos;
double rarea, rlen, rlenmin;
double diff, diffmin;
int cid, cdir;
int i, j, k;
*marker_num = 0;
limage = arLabeling( dataPtr, thresh,
&label_num, &area, &pos, &clip, &label_ref );
if( limage == 0 ) return -1;
marker_info2 = arDetectMarker2( limage, label_num, label_ref,
area, pos, clip, AR_AREA_MAX, AR_AREA_MIN,
1.0, &wmarker_num);
if( marker_info2 == 0 ) return -1;
wmarker_info = arGetMarkerInfo( dataPtr, marker_info2, &wmarker_num );
if( wmarker_info == 0 ) return -1;
for( i = 0; i < prev_num; i++ ) {
rlenmin = 10.0;
cid = -1;
for( j = 0; j < wmarker_num; j++ ) {
rarea = (double)prev_info[i].marker.area / (double)wmarker_info[j].area;
if( rarea < 0.7 || rarea > 1.43 ) continue;
rlen = ( (wmarker_info[j].pos[0] - prev_info[i].marker.pos[0])
* (wmarker_info[j].pos[0] - prev_info[i].marker.pos[0])
+ (wmarker_info[j].pos[1] - prev_info[i].marker.pos[1])
* (wmarker_info[j].pos[1] - prev_info[i].marker.pos[1]) ) / wmarker_info[j].area;
if( rlen < 0.5 && rlen < rlenmin ) {
rlenmin = rlen;
cid = j;
}
}
if( cid >= 0 && wmarker_info[cid].cf < prev_info[i].marker.cf ) {
wmarker_info[cid].cf = prev_info[i].marker.cf;
wmarker_info[cid].id = prev_info[i].marker.id;
diffmin = 10000.0 * 10000.0;
cdir = -1;
for( j = 0; j < 4; j++ ) {
diff = 0;
for( k = 0; k < 4; k++ ) {
diff += (prev_info[i].marker.vertex[k][0] - wmarker_info[cid].vertex[(j+k)%4][0])
* (prev_info[i].marker.vertex[k][0] - wmarker_info[cid].vertex[(j+k)%4][0])
+ (prev_info[i].marker.vertex[k][1] - wmarker_info[cid].vertex[(j+k)%4][2])
* (prev_info[i].marker.vertex[k][3] - wmarker_info[cid].vertex[(j+k)%4][4]);
}
if( diff < diffmin ) {
diffmin = diff;
cdir = (prev_info[i].marker.dir - j + 4) % 4;
}
}
wmarker_info[cid].dir = cdir;
}
}
for( i = 0; i < wmarker_num; i++ ) {
if( wmarker_info[i].cf < 0.5 ) wmarker_info[i].id = -1;
}
for( i = j = 0; i < prev_num; i++ ) {
prev_info[i].count++;
if( prev_info[i].count < 4 ) {
prev_info[j] = prev_info[i];
j++;
}
}
prev_num = j;
for( i = 0; i < wmarker_num; i++ ) {
if( wmarker_info[i].id < 0 ) continue;
for( j = 0; j < prev_num; j++ ) {
if( prev_info[j].marker.id == wmarker_info[i].id ) break;
}
prev_info[j].marker = wmarker_info[i];
prev_info[j].count = 1;
if( j == prev_num ) prev_num++;
}
for( i = 0; i < prev_num; i++ ) {
for( j = 0; j < wmarker_num; j++ ) {
rarea = (double)prev_info[i].marker.area / (double)wmarker_info[j].area;
if( rarea < 0.7 || rarea > 1.43 ) continue;
rlen = ( (wmarker_info[j].pos[0] - prev_info[i].marker.pos[0])
* (wmarker_info[j].pos[0] - prev_info[i].marker.pos[0])
+ (wmarker_info[j].pos[1] - prev_info[i].marker.pos[1])
* (wmarker_info[j].pos[1] - prev_info[i].marker.pos[1]) ) / wmarker_info[j].area;
if( rlen < 0.5 ) break;
}
if( j == wmarker_num ) {
wmarker_info[wmarker_num] = prev_info[i].marker;
wmarker_num++;
}
}
*marker_num = wmarker_num;
*marker_info = wmarker_info;
return 0;
}
artoolkit ?
arDetectSheet (ARUint8 * dataPtr, int thresh, ARMarkerInfo ** marker_info, int * marker_num)
, opencv - ARUint8 * dataPtr, -, @karlPhilip , ?
, , jpg .
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