Several chessboard detector improvements:

- fixed uninitialized memory access and memory leaks
- extracted several code blocks to separate functions
- updated part of algorithm to use cv::Mat instead of CvMat and IplImage

modules/calib3d/src/checkchessboard.cpp

@@ -46,28 +46,26 @@
 #include <vector>
 #include <algorithm>
 
-//#define DEBUG_WINDOWS
+using namespace cv;
+using namespace std;
 
-#if defined(DEBUG_WINDOWS)
-#  include "opencv2/opencv_modules.hpp"
-#  ifdef HAVE_OPENCV_HIGHGUI
-#    include "opencv2/highgui.hpp"
-#  else
-#    undef DEBUG_WINDOWS
-#  endif
-#endif
-
-int cvCheckChessboardBinary(IplImage* src, CvSize size);
-
-static void icvGetQuadrangleHypotheses(CvSeq* contours, std::vector<std::pair<float, int> >& quads, int class_id)
+static void icvGetQuadrangleHypotheses(const std::vector<std::vector< cv::Point > > & contours, const std::vector< cv::Vec4i > & hierarchy, std::vector<std::pair<float, int> >& quads, int class_id)
 {
     const float min_aspect_ratio = 0.3f;
     const float max_aspect_ratio = 3.0f;
     const float min_box_size = 10.0f;
 
-    for(CvSeq* seq = contours; seq != NULL; seq = seq->h_next)
+    typedef std::vector< std::vector< cv::Point > >::const_iterator iter_t;
+    iter_t i;
+    for (i = contours.begin(); i != contours.end(); ++i)
     {
-        CvBox2D box = cvMinAreaRect2(seq);
+        const iter_t::difference_type idx = i - contours.begin();
+        if (hierarchy.at(idx)[3] != -1)
+            continue; // skip holes
+
+        const std::vector< cv::Point > & c = *i;
+        cv::RotatedRect box = cv::minAreaRect(c);
+
         float box_size = MAX(box.size.width, box.size.height);
         if(box_size < min_box_size)
         {
@@ -98,71 +96,28 @@ inline bool less_pred(const std::pair<float, int>& p1, const std::pair<float, in
     return p1.first < p2.first;
 }
 
-// does a fast check if a chessboard is in the input image. This is a workaround to
-// a problem of cvFindChessboardCorners being slow on images with no chessboard
-// - src: input image
-// - size: chessboard size
-// Returns 1 if a chessboard can be in this image and findChessboardCorners should be called,
-// 0 if there is no chessboard, -1 in case of error
-int cvCheckChessboard(IplImage* src, CvSize size)
+static void fillQuads(Mat & white, Mat & black, double white_thresh, double black_thresh, vector<pair<float, int> > & quads)
 {
-    if(src->nChannels > 1)
+    Mat thresh;
     {
-        cvError(CV_BadNumChannels, "cvCheckChessboard", "supports single-channel images only",
-                __FILE__, __LINE__);
+        vector< vector<Point> > contours;
+        vector< Vec4i > hierarchy;
+        threshold(white, thresh, white_thresh, 255, THRESH_BINARY);
+        findContours(thresh, contours, hierarchy, RETR_CCOMP, CHAIN_APPROX_SIMPLE);
+        icvGetQuadrangleHypotheses(contours, hierarchy, quads, 1);
     }
 
-    if(src->depth != 8)
     {
-        cvError(CV_BadDepth, "cvCheckChessboard", "supports depth=8 images only",
-                __FILE__, __LINE__);
+        vector< vector<Point> > contours;
+        vector< Vec4i > hierarchy;
+        threshold(black, thresh, black_thresh, 255, THRESH_BINARY_INV);
+        findContours(thresh, contours, hierarchy, RETR_CCOMP, CHAIN_APPROX_SIMPLE);
+        icvGetQuadrangleHypotheses(contours, hierarchy, quads, 0);
     }
+}
 
-    const int erosion_count = 1;
-    const float black_level = 20.f;
-    const float white_level = 130.f;
-    const float black_white_gap = 70.f;
-
-#if defined(DEBUG_WINDOWS)
-    cvNamedWindow("1", 1);
-    cvShowImage("1", src);
-    cvWaitKey(0);
-#endif //DEBUG_WINDOWS
-
-    CvMemStorage* storage = cvCreateMemStorage();
-
-    IplImage* white = cvCloneImage(src);
-    IplImage* black = cvCloneImage(src);
-
-    cvErode(white, white, NULL, erosion_count);
-    cvDilate(black, black, NULL, erosion_count);
-    IplImage* thresh = cvCreateImage(cvGetSize(src), IPL_DEPTH_8U, 1);
-
-    int result = 0;
-    for(float thresh_level = black_level; thresh_level < white_level && !result; thresh_level += 20.0f)
-    {
-        cvThreshold(white, thresh, thresh_level + black_white_gap, 255, CV_THRESH_BINARY);
-
-#if defined(DEBUG_WINDOWS)
-        cvShowImage("1", thresh);
-        cvWaitKey(0);
-#endif //DEBUG_WINDOWS
-
-        CvSeq* first = 0;
-        std::vector<std::pair<float, int> > quads;
-        cvFindContours(thresh, storage, &first, sizeof(CvContour), CV_RETR_CCOMP);
-        icvGetQuadrangleHypotheses(first, quads, 1);
-
-        cvThreshold(black, thresh, thresh_level, 255, CV_THRESH_BINARY_INV);
-
-#if defined(DEBUG_WINDOWS)
-        cvShowImage("1", thresh);
-        cvWaitKey(0);
-#endif //DEBUG_WINDOWS
-
-        cvFindContours(thresh, storage, &first, sizeof(CvContour), CV_RETR_CCOMP);
-        icvGetQuadrangleHypotheses(first, quads, 0);
-
+static bool checkQuads(vector<pair<float, int> > & quads, const cv::Size & size)
+{
     const size_t min_quads_count = size.width*size.height/2;
     std::sort(quads.begin(), quads.end(), less_pred);
 
@@ -193,18 +148,46 @@ int cvCheckChessboard(IplImage* src, CvSize size)
             {
                 continue;
             }
-                result = 1;
-                break;
-            }
+            return true;
         }
     }
+    return false;
+}
 
+// does a fast check if a chessboard is in the input image. This is a workaround to
+// a problem of cvFindChessboardCorners being slow on images with no chessboard
+// - src: input image
+// - size: chessboard size
+// Returns 1 if a chessboard can be in this image and findChessboardCorners should be called,
+// 0 if there is no chessboard, -1 in case of error
+int cvCheckChessboard(IplImage* src, CvSize size)
+{
+    cv::Mat img = cv::cvarrToMat(src);
+    return checkChessboard(img, size);
+}
+
+int checkChessboard(const cv::Mat & img, const cv::Size & size)
+{
+    CV_Assert(img.channels() == 1 && img.depth() == CV_8U);
+
+    const int erosion_count = 1;
+    const float black_level = 20.f;
+    const float white_level = 130.f;
+    const float black_white_gap = 70.f;
 
-    cvReleaseImage(&thresh);
-    cvReleaseImage(&white);
-    cvReleaseImage(&black);
-    cvReleaseMemStorage(&storage);
+    Mat white;
+    Mat black;
+    erode(img, white, Mat(), Point(-1, -1), erosion_count);
+    dilate(img, black, Mat(), Point(-1, -1), erosion_count);
 
+    int result = 0;
+    for(float thresh_level = black_level; thresh_level < white_level && !result; thresh_level += 20.0f)
+    {
+        vector<pair<float, int> > quads;
+        fillQuads(white, black, thresh_level + black_white_gap, thresh_level, quads);
+        if (checkQuads(quads, size))
+            result = 1;
+    }
     return result;
 }
 
@@ -214,28 +197,14 @@ int cvCheckChessboard(IplImage* src, CvSize size)
 // - size: chessboard size
 // Returns 1 if a chessboard can be in this image and findChessboardCorners should be called,
 // 0 if there is no chessboard, -1 in case of error
-int cvCheckChessboardBinary(IplImage* src, CvSize size)
+int checkChessboardBinary(const cv::Mat & img, const cv::Size & size)
 {
-    if(src->nChannels > 1)
-    {
-        cvError(CV_BadNumChannels, "cvCheckChessboard", "supports single-channel images only",
-                __FILE__, __LINE__);
-    }
+    CV_Assert(img.channels() == 1 && img.depth() == CV_8U);
 
-    if(src->depth != 8)
-    {
-        cvError(CV_BadDepth, "cvCheckChessboard", "supports depth=8 images only",
-                __FILE__, __LINE__);
-    }
-
-    CvMemStorage* storage = cvCreateMemStorage();
-
-    IplImage* white = cvCloneImage(src);
-    IplImage* black = cvCloneImage(src);
-    IplImage* thresh = cvCreateImage(cvGetSize(src), IPL_DEPTH_8U, 1);
+    Mat white = img.clone();
+    Mat black = img.clone();
 
     int result = 0;
-
     for ( int erosion_count = 0; erosion_count <= 3; erosion_count++ )
     {
         if ( 1 == result )
@@ -243,61 +212,14 @@ int cvCheckChessboardBinary(IplImage* src, CvSize size)
 
         if ( 0 != erosion_count ) // first iteration keeps original images
         {
-        cvErode(white, white, NULL, 1);
-        cvDilate(black, black, NULL, 1);
-      }
-
-      cvThreshold(white, thresh, 128, 255, CV_THRESH_BINARY);
-
-      CvSeq* first = 0;
-      std::vector<std::pair<float, int> > quads;
-      cvFindContours(thresh, storage, &first, sizeof(CvContour), CV_RETR_CCOMP);
-      icvGetQuadrangleHypotheses(first, quads, 1);
-
-      cvThreshold(black, thresh, 128, 255, CV_THRESH_BINARY_INV);
-      cvFindContours(thresh, storage, &first, sizeof(CvContour), CV_RETR_CCOMP);
-      icvGetQuadrangleHypotheses(first, quads, 0);
-
-      const size_t min_quads_count = size.width*size.height/2;
-      std::sort(quads.begin(), quads.end(), less_pred);
-
-      // now check if there are many hypotheses with similar sizes
-      // do this by floodfill-style algorithm
-      const float size_rel_dev = 0.4f;
-
-      for(size_t i = 0; i < quads.size(); i++)
-      {
-          size_t j = i + 1;
-          for(; j < quads.size(); j++)
-          {
-              if(quads[j].first/quads[i].first > 1.0f + size_rel_dev)
-              {
-                  break;
-              }
+            erode(white, white, Mat(), Point(-1, -1), 1);
+            dilate(black, black, Mat(), Point(-1, -1), 1);
         }
 
-          if(j + 1 > min_quads_count + i)
-          {
-              // check the number of black and white squares
-              std::vector<int> counts;
-              countClasses(quads, i, j, counts);
-              const int black_count = cvRound(ceil(size.width/2.0)*ceil(size.height/2.0));
-              const int white_count = cvRound(floor(size.width/2.0)*floor(size.height/2.0));
-              if(counts[0] < black_count*0.75 ||
-                 counts[1] < white_count*0.75)
-              {
-                continue;
-              }
+        vector<pair<float, int> > quads;
+        fillQuads(white, black, 128, 128, quads);
+        if (checkQuads(quads, size))
             result = 1;
-              break;
-          }
     }
-    }
-
-    cvReleaseImage(&thresh);
-    cvReleaseImage(&white);
-    cvReleaseImage(&black);
-    cvReleaseMemStorage(&storage);
-
     return result;
 }

modules/calib3d/src/precomp.hpp

@@ -117,4 +117,7 @@ template<typename T> inline int compressElems( T* ptr, const uchar* mask, int ms
 
 }
 
+int checkChessboard(const cv::Mat & img, const cv::Size & size);
+int checkChessboardBinary(const cv::Mat & img, const cv::Size & size);
+
 #endif

modules/calib3d/test/test_chesscorners.cpp

@@ -51,29 +51,31 @@ using namespace cv;
 
 #define _L2_ERR
 
-void show_points( const Mat& gray, const Mat& u, const vector<Point2f>& v, Size pattern_size, bool was_found )
+//#define DEBUG_CHESSBOARD
+
+#ifdef DEBUG_CHESSBOARD
+#include "opencv2/highgui.hpp"
+void show_points( const Mat& gray, const Mat& expected, const vector<Point2f>& actual, bool was_found )
 {
     Mat rgb( gray.size(), CV_8U);
     merge(vector<Mat>(3, gray), rgb);
 
-    for(size_t i = 0; i < v.size(); i++ )
-        circle( rgb, v[i], 3, Scalar(255, 0, 0), FILLED);
+    for(size_t i = 0; i < actual.size(); i++ )
+        circle( rgb, actual[i], 5, Scalar(0, 0, 200), 1, LINE_AA);
 
-    if( !u.empty() )
+    if( !expected.empty() )
     {
-        const Point2f* u_data = u.ptr<Point2f>();
-        size_t count = u.cols * u.rows;
+        const Point2f* u_data = expected.ptr<Point2f>();
+        size_t count = expected.cols * expected.rows;
         for(size_t i = 0; i < count; i++ )
-            circle( rgb, u_data[i], 3, Scalar(0, 255, 0), FILLED);
+            circle(rgb, u_data[i], 4, Scalar(0, 240, 0), 1, LINE_AA);
     }
-    if (!v.empty())
-    {
-        Mat corners((int)v.size(), 1, CV_32FC2, (void*)&v[0]);
-        drawChessboardCorners( rgb, pattern_size, corners, was_found );
-    }
-    //namedWindow( "test", 0 ); imshow( "test", rgb ); waitKey(0);
+    putText(rgb, was_found ? "FOUND !!!" : "NOT FOUND", Point(5, 20), FONT_HERSHEY_PLAIN, 1, Scalar(0, 240, 0));
+    imshow( "test", rgb ); while ((uchar)waitKey(0) != 'q') {};
 }
-
+#else
+#define show_points(...)
+#endif
 
 enum Pattern { CHESSBOARD, CIRCLES_GRID, ASYMMETRIC_CIRCLES_GRID };
 
@@ -253,7 +255,6 @@ void CV_ChessboardDetectorTest::run_batch( const string& filename )
                 result = findCirclesGrid(gray, pattern_size, v, CALIB_CB_ASYMMETRIC_GRID | algorithmFlags);
                 break;
         }
-        show_points( gray, Mat(), v, pattern_size, result );
 
         if( result ^ doesContatinChessboard || v.size() != count_exp )
         {
@@ -280,7 +281,7 @@ void CV_ChessboardDetectorTest::run_batch( const string& filename )
             if( pattern == CHESSBOARD )
                 cornerSubPix( gray, v, Size(5, 5), Size(-1,-1), TermCriteria(TermCriteria::EPS|TermCriteria::MAX_ITER, 30, 0.1));
             //find4QuadCornerSubpix(gray, v, Size(5, 5));
-            show_points( gray, expected, v, pattern_size, result  );
+            show_points( gray, expected, v, result  );
 #ifndef WRITE_POINTS
     //        printf("called find4QuadCornerSubpix\n");
             err = calcError(v, expected);
@@ -298,6 +299,10 @@ void CV_ChessboardDetectorTest::run_batch( const string& filename )
             max_precise_error = MAX( max_precise_error, err );
 #endif
         }
+        else
+        {
+            show_points( gray, Mat(), v, result );
+        }
 
 #ifdef WRITE_POINTS
         Mat mat_v(pattern_size, CV_32FC2, (void*)&v[0]);

modules/python/test/test_calibration.py

@@ -57,7 +57,7 @@ class calibration_test(NewOpenCVTests):
 
         eps = 0.01
         normCamEps = 10.0
-        normDistEps = 0.001
+        normDistEps = 0.05
 
         cameraMatrixTest = [[ 532.80992189,    0.,          342.4952186 ],
          [   0.,         532.93346422,  233.8879292 ],