Merge pull request #26968 from MaximSmolskiy:fix-Aruco-marker-incorrect-detection-near-image-edge

MaximSmolskiy · web-flow · commit 46dbc57a8655 · 2025-03-12T09:47:49.000+03:00
Fix Aruco marker incorrect detection near image edge #26968 ### Pull Request Readiness Checklist Fix #26922 As I understood the algorithm, at the first stage we search for the contours of the marker several times (adaptive threshold with different windows sizes). Therefore, for the same marker, we get several contours (inner and outer with different sizes due to the different windows sizes). In the second stage, we group the contours for the same marker into one group, from which we take the largest contour as the best candidate (which should best match the border of the marker). The problem is that using the `minDistanceToBorder` parameter, we discard contours at the first stage. Thus, we discard the best candidates most appropriate to the marker border, and inner contours may remain, representing a significantly smaller marker border (which we observe in the issue). But if we use the `minDistanceToBorder` parameter to discard the best candidate of the group at the second stage, then there will be no such problems and we will completely discard markers located too close to the border of the image. See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [x] The PR is proposed to the proper branch - [x] There is a reference to the original bug report and related work - [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [x] The feature is well documented and sample code can be built with the project CMake
diff --git a/modules/objdetect/src/aruco/aruco_detector.cpp b/modules/objdetect/src/aruco/aruco_detector.cpp
@@ -130,10 +130,10 @@ static void _threshold(InputArray _in, OutputArray _out, int winSize, double con
 static void _findMarkerContours(const Mat &in, vector<vector<Point2f> > &candidates,
                                 vector<vector<Point> > &contoursOut, double minPerimeterRate,
                                 double maxPerimeterRate, double accuracyRate,
-                                double minCornerDistanceRate, int minDistanceToBorder, int minSize) {
+                                double minCornerDistanceRate, int minSize) {
 
     CV_Assert(minPerimeterRate > 0 && maxPerimeterRate > 0 && accuracyRate > 0 &&
-              minCornerDistanceRate >= 0 && minDistanceToBorder >= 0);
+              minCornerDistanceRate >= 0);
 
     // calculate maximum and minimum sizes in pixels
     unsigned int minPerimeterPixels =
@@ -171,16 +171,6 @@ static void _findMarkerContours(const Mat &in, vector<vector<Point2f> > &candida
         double minCornerDistancePixels = double(contours[i].size()) * minCornerDistanceRate;
         if(minDistSq < minCornerDistancePixels * minCornerDistancePixels) continue;
 
-        // check if it is too near to the image border
-        bool tooNearBorder = false;
-        for(int j = 0; j < 4; j++) {
-            if(approxCurve[j].x < minDistanceToBorder || approxCurve[j].y < minDistanceToBorder ||
-               approxCurve[j].x > in.cols - 1 - minDistanceToBorder ||
-               approxCurve[j].y > in.rows - 1 - minDistanceToBorder)
-               tooNearBorder = true;
-        }
-        if(tooNearBorder) continue;
-
         // if it passes all the test, add to candidates vector
         vector<Point2f> currentCandidate;
         currentCandidate.resize(4);
@@ -305,7 +295,7 @@ static void _detectInitialCandidates(const Mat &grey, vector<vector<Point2f> > &
             _findMarkerContours(thresh, candidatesArrays[i], contoursArrays[i],
                                 params.minMarkerPerimeterRate, params.maxMarkerPerimeterRate,
                                 params.polygonalApproxAccuracyRate, params.minCornerDistanceRate,
-                                params.minDistanceToBorder, params.minSideLengthCanonicalImg);
+                                params.minSideLengthCanonicalImg);
         }
     });
     // join candidates
@@ -742,7 +732,7 @@ struct ArucoDetector::ArucoDetectorImpl {
         vector<vector<Point2f>> rejectedImgPoints;
         if (DictionaryMode::Single == dictMode) {
             Dictionary& dictionary = dictionaries.at(0);
-            auto selectedCandidates = filterTooCloseCandidates(candidates, contours, dictionary.markerSize);
+            auto selectedCandidates = filterTooCloseCandidates(grey.size(), candidates, contours, dictionary.markerSize);
             candidates.clear();
             contours.clear();
 
@@ -765,7 +755,7 @@ struct ArucoDetector::ArucoDetectorImpl {
                 // copy candidates
                 vector<vector<Point2f>> candidatesCopy = candidates;
                 vector<vector<Point> > contoursCopy = contours;
-                candidatesTreeEntry.second = filterTooCloseCandidates(candidatesCopy, contoursCopy, candidatesTreeEntry.first);
+                candidatesTreeEntry.second = filterTooCloseCandidates(grey.size(), candidatesCopy, contoursCopy, candidatesTreeEntry.first);
             }
             candidates.clear();
             contours.clear();
@@ -872,14 +862,14 @@ struct ArucoDetector::ArucoDetectorImpl {
     }
 
     /**
-     * @brief  FILTER OUT NEAR CANDIDATE PAIRS
+     * @brief FILTER OUT NEAR CANDIDATES PAIRS AND TOO NEAR CANDIDATES TO IMAGE BORDER
      *
-     * save the outter/inner border (i.e. potential candidates) to vector<MarkerCandidateTree>,
+     * save the outer/inner border (i.e. potential candidates) to vector<MarkerCandidateTree>,
      * clear candidates and contours
      */
     vector<MarkerCandidateTree>
-    filterTooCloseCandidates(vector<vector<Point2f> > &candidates, vector<vector<Point> > &contours, int markerSize) {
-        CV_Assert(detectorParams.minMarkerDistanceRate >= 0.);
+    filterTooCloseCandidates(const Size &imageSize, vector<vector<Point2f> > &candidates, vector<vector<Point> > &contours, int markerSize) {
+        CV_Assert(detectorParams.minMarkerDistanceRate >= 0. && detectorParams.minDistanceToBorder >= 0);
         vector<MarkerCandidateTree> candidateTree(candidates.size());
         for(size_t i = 0ull; i < candidates.size(); i++) {
             candidateTree[i] = MarkerCandidateTree(std::move(candidates[i]), std::move(contours[i]));
@@ -940,6 +930,20 @@ struct ArucoDetector::ArucoDetectorImpl {
             else // if detectInvertedMarker==false choose largest contours
                 std::stable_sort(grouped.begin(), grouped.end());
             size_t currId = grouped[0];
+            // check if it is too near to the image border
+            bool tooNearBorder = false;
+            for (const auto& corner : candidateTree[currId].corners) {
+                if (corner.x < detectorParams.minDistanceToBorder ||
+                    corner.y < detectorParams.minDistanceToBorder ||
+                    corner.x > imageSize.width - 1 - detectorParams.minDistanceToBorder ||
+                    corner.y > imageSize.height - 1 - detectorParams.minDistanceToBorder) {
+                    tooNearBorder = true;
+                    break;
+                }
+            }
+            if (tooNearBorder) {
+                continue;
+            }
             isSelectedContours[currId] = true;
             for (size_t i = 1ull; i < grouped.size(); i++) {
                 size_t id = grouped[i];
@@ -952,12 +956,11 @@ struct ArucoDetector::ArucoDetectorImpl {
             }
         }
 
-        vector<MarkerCandidateTree> selectedCandidates(groupedCandidates.size());
-        size_t countSelectedContours = 0ull;
+        vector<MarkerCandidateTree> selectedCandidates;
+        selectedCandidates.reserve(groupedCandidates.size());
         for (size_t i = 0ull; i < candidateTree.size(); i++) {
             if (isSelectedContours[i]) {
-                selectedCandidates[countSelectedContours] = std::move(candidateTree[i]);
-                countSelectedContours++;
+                selectedCandidates.push_back(std::move(candidateTree[i]));
             }
         }
 
