C++中的斑點檢測

Question

我是計算機視覺領域的新手，但我需要在C++中做一個小小的功能，即使在他身上打印某些東西，他們也會檢測到白皮書，並且檢索4個邊的座標是什麼我真的很需要，所以我可以使用這些座標並剪切另一個jpg文件並使用切割圖像作爲opengl紋理。 我不知道如何檢測紙張。 嘗試搜索計算機視覺，並發現我必須對圖像進行閾值處理，然後使用邊緣檢測或哈里斯檢測進行標記，但沒有找到任何教程。 任何人都可以幫助我，或給我看一些可以幫助我的教程嗎？

只要找到這樣的：

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++) { 
    /* 
printf("cf = %g\n", wmarker_info[i].cf); 
    */ 
    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; 
    } 

他的這種使用的ARToolKit檢測標誌物？ 如果我創建一個arDetectSheet（ARUint8 * dataPtr，INT脫粒， ARMarkerInfo ** marker_info，INT * marker_num） 說OpenCV中的形象是ARUint8 * dataPtr誰擁有從網絡攝像頭圖像，並嘗試做@karlPhilip example會這行得通？ 我想檢測紙張，所以我可以有邊緣座標，所以我可以使用這些座標剪切我的JPG文件。 我想要什麼：

Answer 1

Artoolkit用於構建擴增實境應用。它不能做你所描述的，除非這塊paper has something printed in it。

如果您正在考慮一些other framework to do this task，我建議您投資OpenCV。