Merge pull request #2439 from ilya-lavrenov:typo

modules/calib3d/perf/perf_pnp.cpp

@@ -126,7 +126,7 @@ PERF_TEST_P(PointsNum, DISABLED_SolvePnPRansac, testing::Values(4, 3*9, 7*13))
     Mat tvec;
 
 #ifdef HAVE_TBB
-    // limit concurrency to get determenistic result
+    // limit concurrency to get deterministic result
     cv::Ptr<tbb::task_scheduler_init> one_thread = new tbb::task_scheduler_init(1);
 #endif
 

modules/calib3d/test/test_solvepnp_ransac.cpp

@@ -271,7 +271,7 @@ TEST(DISABLED_Calib3d_SolvePnPRansac, concurrency)
     Mat tvec1, tvec2;
 
     {
-        // limit concurrency to get determenistic result
+        // limit concurrency to get deterministic result
         cv::theRNG().state = 20121010;
         cv::Ptr<tbb::task_scheduler_init> one_thread = new tbb::task_scheduler_init(1);
         solvePnPRansac(object, image, camera_mat, dist_coef, rvec1, tvec1);

modules/contrib/src/imagelogpolprojection.cpp

@@ -362,14 +362,14 @@ bool ImageLogPolProjection::_initLogPolarCortexSampling(const double reductionFa
 
     //std::cout<<"ImageLogPolProjection::Starting cortex projection"<<std::endl;
     // compute transformation, get theta and Radius in reagrd of the output sampled pixel
-    double diagonalLenght=sqrt((double)(_outputNBcolumns*_outputNBcolumns+_outputNBrows*_outputNBrows));
+    double diagonalLength=sqrt((double)(_outputNBcolumns*_outputNBcolumns+_outputNBrows*_outputNBrows));
     for (unsigned int radiusIndex=0;radiusIndex<_outputNBcolumns;++radiusIndex)
         for(unsigned int orientationIndex=0;orientationIndex<_outputNBrows;++orientationIndex)
         {
             double x=1.0+sinh(radiusAxis[radiusIndex])*cos(orientationAxis[orientationIndex]);
             double y=sinh(radiusAxis[radiusIndex])*sin(orientationAxis[orientationIndex]);
             // get the input picture coordinate
-            double R=diagonalLenght*sqrt(x*x+y*y)/(5.0+sqrt(x*x+y*y));
+            double R=diagonalLength*sqrt(x*x+y*y)/(5.0+sqrt(x*x+y*y));
             double theta=atan2(y,x);
             // convert input polar coord into cartesian/C compatble coordinate
             unsigned int columnIndex=(unsigned int)(cos(theta)*R)+halfInputColumns;

modules/contrib/src/lda.cpp

@@ -229,7 +229,7 @@ Mat subspaceReconstruct(InputArray _W, InputArray _mean, InputArray _src)
         string error_message = format("Wrong mean shape for the given eigenvector matrix. Expected %d, but was %d.", W.cols, mean.total());
         CV_Error(CV_StsBadArg, error_message);
     }
-    // initalize temporary matrices
+    // initialize temporary matrices
     Mat X, Y;
     // copy data & make sure we are using the correct type
     src.convertTo(Y, W.type());

modules/contrib/src/templatebuffer.hpp

@@ -357,27 +357,27 @@ namespace cv
 
             for (unsigned int i=0;i<this->size();++i)
             {
-                double curentValue=(double)*(bufferPTR++);
+                double currentValue=(double)*(bufferPTR++);
 
                 // updating "closest to the high threshold" pixel value
-                double highValueTest=maxThreshold-curentValue;
+                double highValueTest=maxThreshold-currentValue;
                 if (highValueTest>0)
                 {
                     if (deltaH>highValueTest)
                     {
                         deltaH=highValueTest;
-                        updatedHighValue=curentValue;
+                        updatedHighValue=currentValue;
                     }
                 }
 
                 // updating "closest to the low threshold" pixel value
-                double lowValueTest=curentValue-minThreshold;
+                double lowValueTest=currentValue-minThreshold;
                 if (lowValueTest>0)
                 {
                     if (deltaL>lowValueTest)
                     {
                         deltaL=lowValueTest;
-                        updatedLowValue=curentValue;
+                        updatedLowValue=currentValue;
                     }
                 }
             }

modules/core/include/opencv2/core/core_c.h

@@ -105,7 +105,7 @@ CVAPI(void)  cvResetImageROI( IplImage* image );
 /* Retrieves image ROI */
 CVAPI(CvRect) cvGetImageROI( const IplImage* image );
 
-/* Allocates and initalizes CvMat header */
+/* Allocates and initializes CvMat header */
 CVAPI(CvMat*)  cvCreateMatHeader( int rows, int cols, int type );
 
 #define CV_AUTOSTEP  0x7fffffff

modules/core/src/array.cpp

@@ -2897,7 +2897,7 @@ cvCreateImage( CvSize size, int depth, int channels )
 }
 
 
-// initalize IplImage header, allocated by the user
+// initialize IplImage header, allocated by the user
 CV_IMPL IplImage*
 cvInitImageHeader( IplImage * image, CvSize size, int depth,
                    int channels, int origin, int align )

modules/features2d/doc/feature_detection_and_description.rst

@@ -11,9 +11,9 @@ FAST
 ----
 Detects corners using the FAST algorithm
 
-.. ocv:function:: void FAST( InputArray image, vector<KeyPoint>& keypoints, int threshold, bool nonmaxSupression=true )
+.. ocv:function:: void FAST( InputArray image, vector<KeyPoint>& keypoints, int threshold, bool nonmaxSuppression=true )
 
-.. ocv:function:: void FASTX( InputArray image, vector<KeyPoint>& keypoints, int threshold, bool nonmaxSupression, int type )
+.. ocv:function:: void FASTX( InputArray image, vector<KeyPoint>& keypoints, int threshold, bool nonmaxSuppression, int type )
 
     :param image: grayscale image where keypoints (corners) are detected.
 
@@ -21,7 +21,7 @@ Detects corners using the FAST algorithm
 
     :param threshold: threshold on difference between intensity of the central pixel and pixels of a circle around this pixel.
 
-    :param nonmaxSupression: if true, non-maximum suppression is applied to detected corners (keypoints).
+    :param nonmaxSuppression: if true, non-maximum suppression is applied to detected corners (keypoints).
 
     :param type: one of the three neighborhoods as defined in the paper: ``FastFeatureDetector::TYPE_9_16``, ``FastFeatureDetector::TYPE_7_12``, ``FastFeatureDetector::TYPE_5_8``
 

modules/features2d/include/opencv2/features2d/features2d.hpp

@@ -566,10 +566,10 @@ protected:
 
 //! detects corners using FAST algorithm by E. Rosten
 CV_EXPORTS void FAST( InputArray image, CV_OUT vector<KeyPoint>& keypoints,
-                      int threshold, bool nonmaxSupression=true );
+                      int threshold, bool nonmaxSuppression=true );
 
 CV_EXPORTS void FASTX( InputArray image, CV_OUT vector<KeyPoint>& keypoints,
-                      int threshold, bool nonmaxSupression, int type );
+                      int threshold, bool nonmaxSuppression, int type );
 
 class CV_EXPORTS_W FastFeatureDetector : public FeatureDetector
 {

modules/features2d/src/evaluation.cpp

@@ -128,7 +128,7 @@ public:
 
     Point2f center;
     Scalar ellipse; // 3 elements a, b, c: ax^2+2bxy+cy^2=1
-    Size_<float> axes; // half lenght of elipse axes
+    Size_<float> axes; // half length of ellipse axes
     Size_<float> boundingBox; // half sizes of bounding box which sides are parallel to the coordinate axes
 };
 

modules/gpu/doc/feature_detection_and_description.rst

@@ -24,7 +24,7 @@ Class used for corner detection using the FAST algorithm. ::
         // all features have same size
         static const int FEATURE_SIZE = 7;
 
-        explicit FAST_GPU(int threshold, bool nonmaxSupression = true,
+        explicit FAST_GPU(int threshold, bool nonmaxSuppression = true,
                           double keypointsRatio = 0.05);
 
         void operator ()(const GpuMat& image, const GpuMat& mask, GpuMat& keypoints);
@@ -39,7 +39,7 @@ Class used for corner detection using the FAST algorithm. ::
 
         void release();
 
-        bool nonmaxSupression;
+        bool nonmaxSuppression;
 
         int threshold;
 
@@ -61,11 +61,11 @@ gpu::FAST_GPU::FAST_GPU
 -------------------------------------
 Constructor.
 
-.. ocv:function:: gpu::FAST_GPU::FAST_GPU(int threshold, bool nonmaxSupression = true, double keypointsRatio = 0.05)
+.. ocv:function:: gpu::FAST_GPU::FAST_GPU(int threshold, bool nonmaxSuppression = true, double keypointsRatio = 0.05)
 
     :param threshold: Threshold on difference between intensity of the central pixel and pixels on a circle around this pixel.
 
-    :param nonmaxSupression: If it is true, non-maximum suppression is applied to detected corners (keypoints).
+    :param nonmaxSuppression: If it is true, non-maximum suppression is applied to detected corners (keypoints).
 
     :param keypointsRatio: Inner buffer size for keypoints store is determined as (keypointsRatio * image_width * image_height).
 
@@ -115,7 +115,7 @@ Releases inner buffer memory.
 
 gpu::FAST_GPU::calcKeyPointsLocation
 -------------------------------------
-Find keypoints and compute it's response if ``nonmaxSupression`` is true.
+Find keypoints and compute it's response if ``nonmaxSuppression`` is true.
 
 .. ocv:function:: int gpu::FAST_GPU::calcKeyPointsLocation(const GpuMat& image, const GpuMat& mask)
 
@@ -185,7 +185,7 @@ Class for extracting ORB features and descriptors from an image. ::
         int descriptorSize() const;
 
         void setParams(size_t n_features, const ORB::CommonParams& detector_params);
-        void setFastParams(int threshold, bool nonmaxSupression = true);
+        void setFastParams(int threshold, bool nonmaxSuppression = true);
 
         void release();
 

modules/gpu/include/opencv2/gpu/gpu.hpp

@@ -1580,7 +1580,7 @@ public:
     // all features have same size
     static const int FEATURE_SIZE = 7;
 
-    explicit FAST_GPU(int threshold, bool nonmaxSupression = true, double keypointsRatio = 0.05);
+    explicit FAST_GPU(int threshold, bool nonmaxSuppression = true, double keypointsRatio = 0.05);
 
     //! finds the keypoints using FAST detector
     //! supports only CV_8UC1 images
@@ -1596,19 +1596,19 @@ public:
     //! release temporary buffer's memory
     void release();
 
-    bool nonmaxSupression;
+    bool nonmaxSuppression;
 
     int threshold;
 
     //! max keypoints = keypointsRatio * img.size().area()
     double keypointsRatio;
 
-    //! find keypoints and compute it's response if nonmaxSupression is true
+    //! find keypoints and compute it's response if nonmaxSuppression is true
     //! return count of detected keypoints
     int calcKeyPointsLocation(const GpuMat& image, const GpuMat& mask);
 
     //! get final array of keypoints
-    //! performs nonmax supression if needed
+    //! performs nonmax suppression if needed
     //! return final count of keypoints
     int getKeyPoints(GpuMat& keypoints);
 
@@ -1670,10 +1670,10 @@ public:
     //! returns the descriptor size in bytes
     inline int descriptorSize() const { return kBytes; }
 
-    inline void setFastParams(int threshold, bool nonmaxSupression = true)
+    inline void setFastParams(int threshold, bool nonmaxSuppression = true)
     {
         fastDetector_.threshold = threshold;
-        fastDetector_.nonmaxSupression = nonmaxSupression;
+        fastDetector_.nonmaxSuppression = nonmaxSuppression;
     }
 
     //! release temporary buffer's memory

modules/gpu/perf/perf_features2d.cpp

@@ -49,9 +49,9 @@ using namespace perf;
 //////////////////////////////////////////////////////////////////////
 // FAST
 
-DEF_PARAM_TEST(Image_Threshold_NonMaxSupression, string, int, bool);
+DEF_PARAM_TEST(Image_Threshold_NonMaxSuppression, string, int, bool);
 
-PERF_TEST_P(Image_Threshold_NonMaxSupression, Features2D_FAST,
+PERF_TEST_P(Image_Threshold_NonMaxSuppression, Features2D_FAST,
             Combine(Values<string>("gpu/perf/aloe.png"),
                     Values(20),
                     Bool()))

modules/gpu/perf/perf_imgproc.cpp

@@ -1746,7 +1746,7 @@ PERF_TEST_P(Image, ImgProc_HoughLinesP,
     const float rho = 1.0f;
     const float theta = static_cast<float>(CV_PI / 180.0);
     const int threshold = 100;
-    const int minLineLenght = 50;
+    const int minLineLength = 50;
     const int maxLineGap = 5;
 
     const cv::Mat image = cv::imread(fileName, cv::IMREAD_GRAYSCALE);
@@ -1761,7 +1761,7 @@ PERF_TEST_P(Image, ImgProc_HoughLinesP,
         cv::gpu::GpuMat d_lines;
         cv::gpu::HoughLinesBuf d_buf;
 
-        TEST_CYCLE() cv::gpu::HoughLinesP(d_mask, d_lines, d_buf, rho, theta, minLineLenght, maxLineGap);
+        TEST_CYCLE() cv::gpu::HoughLinesP(d_mask, d_lines, d_buf, rho, theta, minLineLength, maxLineGap);
 
         cv::Mat gpu_lines(d_lines);
         cv::Vec4i* begin = gpu_lines.ptr<cv::Vec4i>();
@@ -1773,7 +1773,7 @@ PERF_TEST_P(Image, ImgProc_HoughLinesP,
     {
         std::vector<cv::Vec4i> cpu_lines;
 
-        TEST_CYCLE() cv::HoughLinesP(mask, cpu_lines, rho, theta, threshold, minLineLenght, maxLineGap);
+        TEST_CYCLE() cv::HoughLinesP(mask, cpu_lines, rho, theta, threshold, minLineLength, maxLineGap);
 
         SANITY_CHECK(cpu_lines);
     }

modules/gpu/perf4au/main.cpp

@@ -74,7 +74,7 @@ PERF_TEST_P(Image, HoughLinesP, testing::Values(std::string("im1_1280x800.jpg"))
     const float rho = 1.f;
     const float theta = 1.f;
     const int threshold = 40;
-    const int minLineLenght = 20;
+    const int minLineLength = 20;
     const int maxLineGap = 5;
 
     cv::Mat image = cv::imread(fileName, cv::IMREAD_GRAYSCALE);
@@ -85,11 +85,11 @@ PERF_TEST_P(Image, HoughLinesP, testing::Values(std::string("im1_1280x800.jpg"))
         cv::gpu::GpuMat d_lines;
         cv::gpu::HoughLinesBuf d_buf;
 
-        cv::gpu::HoughLinesP(d_image, d_lines, d_buf, rho, theta, minLineLenght, maxLineGap);
+        cv::gpu::HoughLinesP(d_image, d_lines, d_buf, rho, theta, minLineLength, maxLineGap);
 
         TEST_CYCLE()
         {
-            cv::gpu::HoughLinesP(d_image, d_lines, d_buf, rho, theta, minLineLenght, maxLineGap);
+            cv::gpu::HoughLinesP(d_image, d_lines, d_buf, rho, theta, minLineLength, maxLineGap);
         }
     }
     else
@@ -98,11 +98,11 @@ PERF_TEST_P(Image, HoughLinesP, testing::Values(std::string("im1_1280x800.jpg"))
         cv::Canny(image, mask, 50, 100);
 
         std::vector<cv::Vec4i> lines;
-        cv::HoughLinesP(mask, lines, rho, theta, threshold, minLineLenght, maxLineGap);
+        cv::HoughLinesP(mask, lines, rho, theta, threshold, minLineLength, maxLineGap);
 
         TEST_CYCLE()
         {
-            cv::HoughLinesP(mask, lines, rho, theta, threshold, minLineLenght, maxLineGap);
+            cv::HoughLinesP(mask, lines, rho, theta, threshold, minLineLength, maxLineGap);
         }
     }
 

modules/gpu/src/cuda/fast.cu

@@ -318,9 +318,9 @@ namespace cv { namespace gpu { namespace device
         }
 
         ///////////////////////////////////////////////////////////////////////////
-        // nonmaxSupression
+        // nonmaxSuppression
 
-        __global__ void nonmaxSupression(const short2* kpLoc, int count, const PtrStepSzi scoreMat, short2* locFinal, float* responseFinal)
+        __global__ void nonmaxSuppression(const short2* kpLoc, int count, const PtrStepSzi scoreMat, short2* locFinal, float* responseFinal)
         {
             #if defined(__CUDA_ARCH__) && (__CUDA_ARCH__ >= 110)
 
@@ -356,7 +356,7 @@ namespace cv { namespace gpu { namespace device
             #endif
         }
 
-        int nonmaxSupression_gpu(const short2* kpLoc, int count, PtrStepSzi score, short2* loc, float* response)
+        int nonmaxSuppression_gpu(const short2* kpLoc, int count, PtrStepSzi score, short2* loc, float* response)
         {
             void* counter_ptr;
             cudaSafeCall( cudaGetSymbolAddress(&counter_ptr, g_counter) );
@@ -368,7 +368,7 @@ namespace cv { namespace gpu { namespace device
 
             cudaSafeCall( cudaMemset(counter_ptr, 0, sizeof(unsigned int)) );
 
-            nonmaxSupression<<<grid, block>>>(kpLoc, count, score, loc, response);
+            nonmaxSuppression<<<grid, block>>>(kpLoc, count, score, loc, response);
             cudaSafeCall( cudaGetLastError() );
 
             cudaSafeCall( cudaDeviceSynchronize() );

modules/gpu/src/fast.cpp

@@ -59,8 +59,8 @@ int cv::gpu::FAST_GPU::getKeyPoints(GpuMat&) { throw_nogpu(); return 0; }
 
 #else /* !defined (HAVE_CUDA) */
 
-cv::gpu::FAST_GPU::FAST_GPU(int _threshold, bool _nonmaxSupression, double _keypointsRatio) :
-    nonmaxSupression(_nonmaxSupression), threshold(_threshold), keypointsRatio(_keypointsRatio), count_(0)
+cv::gpu::FAST_GPU::FAST_GPU(int _threshold, bool _nonmaxSuppression, double _keypointsRatio) :
+    nonmaxSuppression(_nonmaxSuppression), threshold(_threshold), keypointsRatio(_keypointsRatio), count_(0)
 {
 }
 
@@ -114,7 +114,7 @@ namespace cv { namespace gpu { namespace device
     namespace fast
     {
         int calcKeypoints_gpu(PtrStepSzb img, PtrStepSzb mask, short2* kpLoc, int maxKeypoints, PtrStepSzi score, int threshold);
-        int nonmaxSupression_gpu(const short2* kpLoc, int count, PtrStepSzi score, short2* loc, float* response);
+        int nonmaxSuppression_gpu(const short2* kpLoc, int count, PtrStepSzi score, short2* loc, float* response);
     }
 }}}
 
@@ -129,13 +129,13 @@ int cv::gpu::FAST_GPU::calcKeyPointsLocation(const GpuMat& img, const GpuMat& ma
 
     ensureSizeIsEnough(1, maxKeypoints, CV_16SC2, kpLoc_);
 
-    if (nonmaxSupression)
+    if (nonmaxSuppression)
     {
         ensureSizeIsEnough(img.size(), CV_32SC1, score_);
         score_.setTo(Scalar::all(0));
     }
 
-    count_ = calcKeypoints_gpu(img, mask, kpLoc_.ptr<short2>(), maxKeypoints, nonmaxSupression ? score_ : PtrStepSzi(), threshold);
+    count_ = calcKeypoints_gpu(img, mask, kpLoc_.ptr<short2>(), maxKeypoints, nonmaxSuppression ? score_ : PtrStepSzi(), threshold);
     count_ = std::min(count_, maxKeypoints);
 
     return count_;
@@ -150,8 +150,8 @@ int cv::gpu::FAST_GPU::getKeyPoints(GpuMat& keypoints)
 
     ensureSizeIsEnough(ROWS_COUNT, count_, CV_32FC1, keypoints);
 
-    if (nonmaxSupression)
-        return nonmaxSupression_gpu(kpLoc_.ptr<short2>(), count_, score_, keypoints.ptr<short2>(LOCATION_ROW), keypoints.ptr<float>(RESPONSE_ROW));
+    if (nonmaxSuppression)
+        return nonmaxSuppression_gpu(kpLoc_.ptr<short2>(), count_, score_, keypoints.ptr<short2>(LOCATION_ROW), keypoints.ptr<float>(RESPONSE_ROW));
 
     GpuMat locRow(1, count_, kpLoc_.type(), keypoints.ptr(0));
     kpLoc_.colRange(0, count_).copyTo(locRow);

modules/gpu/test/test_features2d.cpp

@@ -52,20 +52,20 @@ using namespace cvtest;
 namespace
 {
     IMPLEMENT_PARAM_CLASS(FAST_Threshold, int)
-    IMPLEMENT_PARAM_CLASS(FAST_NonmaxSupression, bool)
+    IMPLEMENT_PARAM_CLASS(FAST_NonmaxSuppression, bool)
 }
 
-PARAM_TEST_CASE(FAST, cv::gpu::DeviceInfo, FAST_Threshold, FAST_NonmaxSupression)
+PARAM_TEST_CASE(FAST, cv::gpu::DeviceInfo, FAST_Threshold, FAST_NonmaxSuppression)
 {
     cv::gpu::DeviceInfo devInfo;
     int threshold;
-    bool nonmaxSupression;
+    bool nonmaxSuppression;
 
     virtual void SetUp()
     {
         devInfo = GET_PARAM(0);
         threshold = GET_PARAM(1);
-        nonmaxSupression = GET_PARAM(2);
+        nonmaxSuppression = GET_PARAM(2);
 
         cv::gpu::setDevice(devInfo.deviceID());
     }
@@ -77,7 +77,7 @@ GPU_TEST_P(FAST, Accuracy)
     ASSERT_FALSE(image.empty());
 
     cv::gpu::FAST_GPU fast(threshold);
-    fast.nonmaxSupression = nonmaxSupression;
+    fast.nonmaxSuppression = nonmaxSuppression;
 
     if (!supportFeature(devInfo, cv::gpu::GLOBAL_ATOMICS))
     {
@@ -97,7 +97,7 @@ GPU_TEST_P(FAST, Accuracy)
         fast(loadMat(image), cv::gpu::GpuMat(), keypoints);
 
         std::vector<cv::KeyPoint> keypoints_gold;
-        cv::FAST(image, keypoints_gold, threshold, nonmaxSupression);
+        cv::FAST(image, keypoints_gold, threshold, nonmaxSuppression);
 
         ASSERT_KEYPOINTS_EQ(keypoints_gold, keypoints);
     }
@@ -106,7 +106,7 @@ GPU_TEST_P(FAST, Accuracy)
 INSTANTIATE_TEST_CASE_P(GPU_Features2D, FAST, testing::Combine(
     ALL_DEVICES,
     testing::Values(FAST_Threshold(25), FAST_Threshold(50)),
-    testing::Values(FAST_NonmaxSupression(false), FAST_NonmaxSupression(true))));
+    testing::Values(FAST_NonmaxSuppression(false), FAST_NonmaxSuppression(true))));
 
 /////////////////////////////////////////////////////////////////////////////////////////////////
 // ORB

modules/highgui/src/window_QT.cpp

@@ -1536,7 +1536,7 @@ CvWindow::CvWindow(QString name, int arg2)
     setWindowTitle(name);
         setObjectName(name);
 
-        setFocus( Qt::PopupFocusReason ); //#1695 arrow keys are not recieved without the explicit focus
+        setFocus( Qt::PopupFocusReason ); //#1695 arrow keys are not received without the explicit focus
 
     resize(400, 300);
     setMinimumSize(1, 1);

modules/highgui/src/window_carbon.cpp

@@ -569,7 +569,7 @@ static int icvCreateTrackbar (const char* trackbar_name,
 
         //pad size maxvalue in pixel
         Point	qdSize;
-        char valueinchar[strlen(trackbar_name)+1 +1 +1+nbDigit+1];//lenght+\n +space +(+nbDigit+)
+        char valueinchar[strlen(trackbar_name)+1 +1 +1+nbDigit+1];//length+\n +space +(+nbDigit+)
         sprintf(valueinchar, "%s (%d)",trackbar_name, trackbar->maxval);
         SInt16	baseline;
         CFStringRef text = CFStringCreateWithCString(NULL,valueinchar,kCFStringEncodingASCII);

modules/imgproc/doc/feature_detection.rst

@@ -101,7 +101,7 @@ Harris edge detector.
 
 .. ocv:pyfunction:: cv2.cornerHarris(src, blockSize, ksize, k[, dst[, borderType]]) -> dst
 
-.. ocv:cfunction:: void cvCornerHarris( const CvArr* image, CvArr* harris_responce, int block_size, int aperture_size=3, double k=0.04 )
+.. ocv:cfunction:: void cvCornerHarris( const CvArr* image, CvArr* harris_response, int block_size, int aperture_size=3, double k=0.04 )
 
 .. ocv:pyoldfunction:: cv.CornerHarris(image, harris_dst, blockSize, aperture_size=3, k=0.04) -> None
 

modules/imgproc/include/opencv2/imgproc/imgproc_c.h

@@ -304,7 +304,7 @@ CVAPI(int)  cvFindContours( CvArr* image, CvMemStorage* storage, CvSeq** first_c
                             int method CV_DEFAULT(CV_CHAIN_APPROX_SIMPLE),
                             CvPoint offset CV_DEFAULT(cvPoint(0,0)));
 
-/* Initalizes contour retrieving process.
+/* Initializes contour retrieving process.
    Calls cvStartFindContours.
    Calls cvFindNextContour until null pointer is returned
    or some other condition becomes true.
@@ -334,7 +334,7 @@ CVAPI(CvSeq*) cvApproxChains( CvSeq* src_seq, CvMemStorage* storage,
                             int  minimal_perimeter CV_DEFAULT(0),
                             int  recursive CV_DEFAULT(0));
 
-/* Initalizes Freeman chain reader.
+/* Initializes Freeman chain reader.
    The reader is used to iteratively get coordinates of all the chain points.
    If the Freeman codes should be read as is, a simple sequence reader should be used */
 CVAPI(void) cvStartReadChainPoints( CvChain* chain, CvChainPtReader* reader );
@@ -573,7 +573,7 @@ CVAPI(void)  cvCornerMinEigenVal( const CvArr* image, CvArr* eigenval,
 
 /* Harris corner detector:
    Calculates det(M) - k*(trace(M)^2), where M is 2x2 gradient covariation matrix for each pixel */
-CVAPI(void)  cvCornerHarris( const CvArr* image, CvArr* harris_responce,
+CVAPI(void)  cvCornerHarris( const CvArr* image, CvArr* harris_response,
                              int block_size, int aperture_size CV_DEFAULT(3),
                              double k CV_DEFAULT(0.04) );
 

modules/imgproc/src/approx.cpp

@@ -220,7 +220,7 @@ CvSeq* icvApproximateChainTC89( CvChain* chain, int header_size,
     current = temp.next;
 
     /* Pass 2.
-       Performs non-maxima supression */
+       Performs non-maxima suppression */
     do
     {
         int k2 = current->k >> 1;

modules/imgproc/src/canny.cpp

@@ -171,7 +171,7 @@ void cv::Canny( InputArray _src, OutputArray _dst,
     #define CANNY_PUSH(d)    *(d) = uchar(2), *stack_top++ = (d)
     #define CANNY_POP(d)     (d) = *--stack_top
 
-    // calculate magnitude and angle of gradient, perform non-maxima supression.
+    // calculate magnitude and angle of gradient, perform non-maxima suppression.
     // fill the map with one of the following values:
     //   0 - the pixel might belong to an edge
     //   1 - the pixel can not belong to an edge

modules/ocl/src/opencl/haarobjectdetect.cl

@@ -217,7 +217,7 @@ __kernel void gpuRunHaarClassifierCascadePacked(
                 (SumL[M0(n0.x)+lcl_off] - SumL[M1(n0.x)+lcl_off] - SumL[M0(n0.y)+lcl_off] + SumL[M1(n0.y)+lcl_off]) * as_float(n1.z) +
                 (SumL[M0(n0.z)+lcl_off] - SumL[M1(n0.z)+lcl_off] - SumL[M0(n0.w)+lcl_off] + SumL[M1(n0.w)+lcl_off]) * as_float(n1.w) +
                 (SumL[M0(n1.x)+lcl_off] - SumL[M1(n1.x)+lcl_off] - SumL[M0(n1.y)+lcl_off] + SumL[M1(n1.y)+lcl_off]) * as_float(n2.x);
-            //accumulate stage responce
+            //accumulate stage response
             stage_sum += (classsum >= nodethreshold) ? as_float(n2.w) : as_float(n2.z);
         }
         result = (stage_sum >= stagethreshold);

modules/ts/include/opencv2/ts/ts.hpp

@@ -372,7 +372,7 @@ public:
         // processing time (in this case there should be possibility to interrupt such a function
         FAIL_HANG=-13,
 
-        // unexpected responce on passing bad arguments to the tested function
+        // unexpected response on passing bad arguments to the tested function
         // (the function crashed, proceed succesfully (while it should not), or returned
         // error code that is different from what is expected)
         FAIL_BAD_ARG_CHECK=-14,

modules/viz/doc/widget.rst

@@ -397,7 +397,7 @@ This 3D Widget defines a cone. ::
     {
     public:
         //! create default cone, oriented along x-axis with center of its base located at origin
-        WCone(double lenght, double radius, int resolution = 6.0, const Color &color = Color::white());
+        WCone(double length, double radius, int resolution = 6.0, const Color &color = Color::white());
 
         //! creates repositioned cone
         WCone(double radius, const Point3d& center, const Point3d& tip, int resolution = 6.0, const Color &color = Color::white());

platforms/android/service/engine/src/org/opencv/engine/manager/ManagerActivity.java

@@ -214,12 +214,12 @@ public class ManagerActivity extends Activity
             }
         });
 
-        mPackageChangeReciever = new BroadcastReceiver() {
+        mPackageChangeReceiver = new BroadcastReceiver() {
 
             @Override
             public void onReceive(Context context, Intent intent) {
-                Log.d("OpenCVManager/Reciever", "Bradcast message " + intent.getAction() + " reciever");
-                Log.d("OpenCVManager/Reciever", "Filling package list on broadcast message");
+                Log.d("OpenCVManager/Receiver", "Broadcast message " + intent.getAction() + " receiver");
+                Log.d("OpenCVManager/Receiver", "Filling package list on broadcast message");
                 if (!bindService(new Intent("org.opencv.engine.BIND"), new OpenCVEngineServiceConnection(), Context.BIND_AUTO_CREATE))
                 {
                     TextView EngineVersionView = (TextView)findViewById(R.id.EngineVersionValue);
@@ -235,14 +235,14 @@ public class ManagerActivity extends Activity
         filter.addAction(Intent.ACTION_PACKAGE_REMOVED);
         filter.addAction(Intent.ACTION_PACKAGE_REPLACED);
 
-        registerReceiver(mPackageChangeReciever, filter);
+        registerReceiver(mPackageChangeReceiver, filter);
     }
 
     @Override
     protected void onDestroy() {
         super.onDestroy();
-        if (mPackageChangeReciever != null)
-            unregisterReceiver(mPackageChangeReciever);
+        if (mPackageChangeReceiver != null)
+            unregisterReceiver(mPackageChangeReceiver);
     }
 
     @Override
@@ -273,7 +273,7 @@ public class ManagerActivity extends Activity
     protected int ManagerApiLevel = 0;
     protected String ManagerVersion;
 
-    protected BroadcastReceiver mPackageChangeReciever = null;
+    protected BroadcastReceiver mPackageChangeReceiver = null;
 
     protected class OpenCVEngineServiceConnection implements ServiceConnection
     {

samples/cpp/morphology2.cpp

@@ -12,7 +12,7 @@ static void help()
 
 printf("\nShow off image morphology: erosion, dialation, open and close\n"
     "Call:\n   morphology2 [image]\n"
-    "This program also shows use of rect, elipse and cross kernels\n\n");
+    "This program also shows use of rect, ellipse and cross kernels\n\n");
 printf( "Hot keys: \n"
     "\tESC - quit the program\n"
     "\tr - use rectangle structuring element\n"

samples/gpu/morphology.cpp

@@ -13,7 +13,7 @@ static void help()
 
 printf("\nShow off image morphology: erosion, dialation, open and close\n"
     "Call:\n   morphology2 [image]\n"
-    "This program also shows use of rect, elipse and cross kernels\n\n");
+    "This program also shows use of rect, ellipse and cross kernels\n\n");
 printf( "Hot keys: \n"
     "\tESC - quit the program\n"
     "\tr - use rectangle structuring element\n"