CvMat cvmat_remove_column(const CvMat*mat, int column)
{
    assert(column<mat->cols && column>=0);
    assert(mat->cols > 1);

    CvMat new_mat = cvMat(mat->rows, mat->cols-1, mat->type, malloc(mat->rows*mat->cols*8));
    int t;
    int size = CV_ELEM_SIZE(mat->type);
    for(t=0;t<mat->rows;t++) {
        int pos = 0;
        int s;
        for(s=0;s<mat->cols;s++) {
            if(s!=column) {
                memcpy(CV_MAT_ELEM_PTR(new_mat, t, pos), CV_MAT_ELEM_PTR((*mat), t, s), size);
                pos++;
            }
        }
    }
    return new_mat;
}

/*
m_buf只在readHeader中被使用
*/
bool  JpegDecoder::readHeader()
{
    bool result = false;
    close();

    JpegState* state = new JpegState;
    m_state = state;
    state->cinfo.err = jpeg_std_error(&state->jerr.pub);
    state->jerr.pub.error_exit = error_exit;

    if( setjmp( state->jerr.setjmp_buffer ) == 0 )
    {
        jpeg_create_decompress( &state->cinfo );

        if( !(m_buf.data.ptr == 0) )
        {
            jpeg_buffer_src(&state->cinfo, &state->source);
            state->source.pub.next_input_byte = m_buf.data.ptr;
            //state->source.pub.bytes_in_buffer = m_buf.cols*m_buf.rows*m_buf.elemSize();//+++CV_ELEM_SIZE
			state->source.pub.bytes_in_buffer = m_buf.cols*m_buf.rows*CV_ELEM_SIZE(m_buf.type);//+++CV_ELEM_SIZE
			
        }
        else
        {
            m_f = fopen( m_filename.c_str(), "rb" );
            if( m_f )
                jpeg_stdio_src( &state->cinfo, m_f );
        }
        jpeg_read_header( &state->cinfo, TRUE );

        m_width = state->cinfo.image_width;
        m_height = state->cinfo.image_height;
        m_type = state->cinfo.num_components > 1 ? CV_8UC3 : CV_8UC1;
        result = true;
    }

    if( !result )
        close();

    return result;
}

// Selects sub-array (no data is copied)
CV_IMPL  CvMat*
cvGetSubRect( const CvArr* arr, CvMat* submat, CvRect rect )
{
    CvMat* res = 0;

    CV_FUNCNAME( "cvGetRect" );

    __BEGIN__;

    CvMat stub, *mat = (CvMat*)arr;

    if( !CV_IS_MAT( mat ))
        CV_CALL( mat = cvGetMat( mat, &stub ));

    if( !submat )
        CV_ERROR( CV_StsNullPtr, "" );

    if( (rect.x|rect.y|rect.width|rect.height) < 0 )
        CV_ERROR( CV_StsBadSize, "" );

    if( rect.x + rect.width > mat->cols ||
        rect.y + rect.height > mat->rows )
        CV_ERROR( CV_StsBadSize, "" );

    {
    submat->data.ptr = mat->data.ptr + (size_t)rect.y*mat->step +
                       rect.x*CV_ELEM_SIZE(mat->type);
    submat->step = mat->step & (rect.height > 1 ? -1 : 0);
    submat->type =
        (mat->type & (rect.width < mat->cols ? ~CV_MAT_CONT_FLAG : -1)) |
        (submat->step == 0 ? CV_MAT_CONT_FLAG : 0);
    submat->rows = rect.height;
    submat->cols = rect.width;
    submat->refcount = 0;
    res = submat;
    }

    __END__;

    return res;
}

	CameraRGB(std::string& propertyPrefix, const Ice::PropertiesPtr propIn)
      : prefix(propertyPrefix),
	imageFmt(),
	imageDescription(new jderobot::ImageDescription()),
	cameraDescription(new jderobot::CameraDescription()),
	replyTask()
	{
	Ice::PropertiesPtr prop = propIn;


	//fill cameraDescription
	cameraDescription->name = prop->getProperty(prefix+"Name");
	if (cameraDescription->name.size() == 0)
		jderobot::Logger::getInstance()->warning( "Camera name not configured" );

	cameraDescription->shortDescription = prop->getProperty(prefix + "ShortDescription");

	//fill imageDescription
	imageDescription->width = prop->getPropertyAsIntWithDefault(prefix+"width",5);;
	imageDescription->height = prop->getPropertyAsIntWithDefault(prefix+"height",5);;


	int fps = prop->getPropertyAsIntWithDefault(prefix+"fps",5);
	//we use formats according to colorspaces
	std::string fmtStr = prop->getPropertyWithDefault(prefix+"Format","ImageRGB8");//default format YUY2
	imageFmt = colorspaces::Image::Format::searchFormat(fmtStr);
	if (!imageFmt)
		jderobot::Logger::getInstance()->warning( "Format " + fmtStr + " unknown" );
	imageDescription->size = imageDescription->width * imageDescription->height * CV_ELEM_SIZE(imageFmt->cvType);
	imageDescription->format = imageFmt->name;

	// Set the formats allowed
	mFormats.push_back(colorspaces::ImageRGB8::FORMAT_RGB8.get()->name);



	jderobot::Logger::getInstance()->info( "Starting thread for camera: " + cameraDescription->name );
	replyTask = new ReplyTask(this,fps, mFormats[0]);

	this->control=replyTask->start();//my own thread
	}

CvMat* cvGetSubRect_d( const CvArr* arr, CvMat* submat, CvRect rect )
{
    CvMat* res = 0;
    CvMat stub, *mat = (CvMat*)arr;

    if( !CV_IS_MAT( mat ))
        mat = cvGetMat( mat, &stub );

    if( !submat )
        CV_Error( CV_StsNullPtr, "" );

    if( (rect.x|rect.y|rect.width|rect.height) < 0 )
        CV_Error( CV_StsBadSize, "" );

    if( rect.x + rect.width > mat->cols ||
        rect.y + rect.height > mat->rows )
        CV_Error( CV_StsBadSize, "" );

    {
        /*
           int* refcount = mat->refcount;

           if( refcount )
           ++*refcount;

           cvDecRefData( submat );
           */
        submat->data.ptr = mat->data.ptr + (size_t)rect.y*mat->step +
            rect.x*CV_ELEM_SIZE(mat->type);
        submat->step = mat->step;
        submat->type = (mat->type & (rect.width < mat->cols ? ~CV_MAT_CONT_FLAG : -1)) |
            (rect.height <= 1 ? CV_MAT_CONT_FLAG : 0);
        submat->rows = rect.height;
        submat->cols = rect.width;
        submat->refcount = 0;
        res = submat;
    }

    return res;
}

CV_IMPL CvSeq* cvPointSeqFromMat( int seq_kind, const CvArr* arr,
                                  CvContour* contour_header, CvSeqBlock* block )
{
    CvSeq* contour = 0;

    CV_FUNCNAME( "cvPointSeqFromMat" );

    assert( arr != 0 && contour_header != 0 && block != 0 );

    __BEGIN__;
    
    int eltype;
    CvMat* mat = (CvMat*)arr;
    
    if( !CV_IS_MAT( mat ))
        CV_ERROR( CV_StsBadArg, "Input array is not a valid matrix" ); 

    eltype = CV_MAT_TYPE( mat->type );
    if( eltype != CV_32SC2 && eltype != CV_32FC2 )
        CV_ERROR( CV_StsUnsupportedFormat,
        "The matrix can not be converted to point sequence because of "
        "inappropriate element type" );

    if( (mat->width != 1 && mat->height != 1) || !CV_IS_MAT_CONT(mat->type))
        CV_ERROR( CV_StsBadArg,
        "The matrix converted to point sequence must be "
        "1-dimensional and continuous" );

    CV_CALL( cvMakeSeqHeaderForArray(
            (seq_kind & (CV_SEQ_KIND_MASK|CV_SEQ_FLAG_CLOSED)) | eltype,
            sizeof(CvContour), CV_ELEM_SIZE(eltype), mat->data.ptr,
            mat->width*mat->height, (CvSeq*)contour_header, block ));

    contour = (CvSeq*)contour_header;

    __END__;

    return contour;
}

Mat cvarrToMat(const CvArr* arr, bool copyData,
               bool /*allowND*/, int coiMode, AutoBuffer<double>* abuf )
{
    if( !arr )
        return Mat();
    if( CV_IS_MAT_HDR_Z(arr) )
        return cvMatToMat((const CvMat*)arr, copyData);
    if( CV_IS_MATND(arr) )
        return cvMatNDToMat((const CvMatND*)arr, copyData );
    if( CV_IS_IMAGE(arr) )
    {
        const IplImage* iplimg = (const IplImage*)arr;
        if( coiMode == 0 && iplimg->roi && iplimg->roi->coi > 0 )
            CV_Error(CV_BadCOI, "COI is not supported by the function");
        return iplImageToMat(iplimg, copyData);
    }
    if( CV_IS_SEQ(arr) )
    {
        CvSeq* seq = (CvSeq*)arr;
        int total = seq->total, type = CV_MAT_TYPE(seq->flags), esz = seq->elem_size;
        if( total == 0 )
            return Mat();
        CV_Assert(total > 0 && CV_ELEM_SIZE(seq->flags) == esz);
        if(!copyData && seq->first->next == seq->first)
            return Mat(total, 1, type, seq->first->data);
        if( abuf )
        {
            abuf->allocate(((size_t)total*esz + sizeof(double)-1)/sizeof(double));
            double* bufdata = abuf->data();
            cvCvtSeqToArray(seq, bufdata, CV_WHOLE_SEQ);
            return Mat(total, 1, type, bufdata);
        }

        Mat buf(total, 1, type);
        cvCvtSeqToArray(seq, buf.ptr(), CV_WHOLE_SEQ);
        return buf;
    }
    CV_Error(CV_StsBadArg, "Unknown array type");
}

void cvArrPrint(CvArr * arr){
  CvMat * mat;
  CvMat stub;

  mat = cvGetMat(arr, &stub);
  
  int cn = CV_MAT_CN(mat->type);
  int depth = CV_MAT_DEPTH(mat->type);
  int step = MAX(mat->step, cn*mat->cols*CV_ELEM_SIZE(depth));


  switch(depth){
    case CV_8U:
      cv_arr_write(stdout, "%u", (uchar *)mat->data.ptr, mat->rows, cn, step);
      break;
    case CV_8S:
      cv_arr_write(stdout, "%d", (char *)mat->data.ptr, mat->rows, cn, step);
      break;
    case CV_16U:
      cv_arr_write(stdout, "%u", (ushort *)mat->data.ptr, mat->rows, cn, step);
      break;
    case CV_16S:
      cv_arr_write(stdout, "%d", (short *)mat->data.ptr, mat->rows, cn, step);
      break;
    case CV_32S:
      cv_arr_write(stdout, "%d", (int *)mat->data.ptr, mat->rows, cn, step);
      break;
    case CV_32F:
      cv_arr_write(stdout, "%f", (float *)mat->data.ptr, mat->rows, cn, step);
      break;
    case CV_64F:
      cv_arr_write(stdout, "%g", (double *)mat->data.ptr, mat->rows, cn, step);
      break;
    default:
      CV_Error( CV_StsError, "Unknown element type");
      break;
  }
}

CV_IMPL int
cvSampleLine( const void* img, CvPoint pt1, CvPoint pt2,
              void* _buffer, int connectivity )
{
    int count = -1;
    
    CV_FUNCNAME( "cvSampleLine" );

    __BEGIN__;
    
    int i, coi = 0, pix_size;
    CvMat stub, *mat = (CvMat*)img;
    CvLineIterator iterator;
    uchar* buffer = (uchar*)_buffer;

    CV_CALL( mat = cvGetMat( mat, &stub, &coi ));

    if( coi != 0 )
        CV_ERROR( CV_BadCOI, "" );

    if( !buffer )
        CV_ERROR( CV_StsNullPtr, "" );

    CV_CALL( count = cvInitLineIterator( mat, pt1, pt2, &iterator, connectivity ));

    pix_size = CV_ELEM_SIZE(mat->type);
    for( i = 0; i < count; i++ )
    {
        for( int j = 0; j < pix_size; j++ )
            buffer[j] = iterator.ptr[j];
        buffer += pix_size;
        CV_NEXT_LINE_POINT( iterator );
    }

    __END__;

    return count;
}

CV_IMPL void
cvDeInterlace( const CvArr* framearr, CvArr* fieldEven, CvArr* fieldOdd )
{
    CV_FUNCNAME("cvDeInterlace");
    
    __BEGIN__;

    CvMat frame_stub, *frame = (CvMat*)framearr;
    CvMat even_stub, *even = (CvMat*)fieldEven;
    CvMat odd_stub, *odd = (CvMat*)fieldOdd;
    CvSize size;
    int y;

    CV_CALL( frame = cvGetMat( frame, &frame_stub ));
    CV_CALL( even = cvGetMat( even, &even_stub ));
    CV_CALL( odd = cvGetMat( odd, &odd_stub ));

    if( !CV_ARE_TYPES_EQ( frame, even ) || !CV_ARE_TYPES_EQ( frame, odd ))
        CV_ERROR( CV_StsUnmatchedFormats, "All the input images must have the same type" );

    if( frame->cols != even->cols || frame->cols != odd->cols ||
        frame->rows != even->rows*2 || odd->rows != even->rows )
        CV_ERROR( CV_StsUnmatchedSizes, "Uncorrelated sizes of the input image and output fields" );

    size = cvGetMatSize( even );
    size.width *= CV_ELEM_SIZE( even->type );

    for( y = 0; y < size.height; y++ )
    {
        memcpy( even->data.ptr + even->step*y,
                frame->data.ptr + frame->step*y*2, size.width );
        memcpy( odd->data.ptr + even->step*y,
                frame->data.ptr + frame->step*(y*2+1), size.width );
    }  

    __END__;
}

// This function create cross-validation EstimateModel.
ML_IMPL CvStatModel*
cvCreateCrossValidationEstimateModel(
    int                samples_all,
    const CvStatModelParams* estimateParams,
    const CvMat*             sampleIdx)
{
    CvStatModel*            model   = NULL;
    CvCrossValidationModel* crVal   = NULL;

    CV_FUNCNAME ("cvCreateCrossValidationEstimateModel");
    __BEGIN__

    int  k_fold = 10;

    int  i, j, k, s_len;
    int  samples_selected;
    CvRNG rng;
    CvRNG* prng;
    int* res_s_data;
    int* te_s_data;
    int* folds;

    rng = cvRNG(cvGetTickCount());
    cvRandInt (&rng);
    cvRandInt (&rng);
    cvRandInt (&rng);
    cvRandInt (&rng);
// Check input parameters.
    if (estimateParams)
        k_fold = ((CvCrossValidationParams*)estimateParams)->k_fold;
    if (!k_fold)
    {
        CV_ERROR (CV_StsBadArg, "Error in parameters of cross-validation (k_fold == 0)!");
    }
    if (samples_all <= 0)
    {
        CV_ERROR (CV_StsBadArg, "<samples_all> should be positive!");
    }

// Alloc memory and fill standart StatModel's fields.
    CV_CALL (crVal = (CvCrossValidationModel*)cvCreateStatModel (
                         CV_STAT_MODEL_MAGIC_VAL | CV_CROSSVAL_MAGIC_VAL,
                         sizeof(CvCrossValidationModel),
                         cvReleaseCrossValidationModel,
                         NULL, NULL));
    crVal->current_fold    = -1;
    crVal->folds_all       = k_fold;
    if (estimateParams && ((CvCrossValidationParams*)estimateParams)->is_regression)
        crVal->is_regression = 1;
    else
        crVal->is_regression = 0;
    if (estimateParams && ((CvCrossValidationParams*)estimateParams)->rng)
        prng = ((CvCrossValidationParams*)estimateParams)->rng;
    else
        prng = &rng;

    // Check and preprocess sample indices.
    if (sampleIdx)
    {
        int s_step;
        int s_type = 0;

        if (!CV_IS_MAT (sampleIdx))
            CV_ERROR (CV_StsBadArg, "Invalid sampleIdx array");

        if (sampleIdx->rows != 1 && sampleIdx->cols != 1)
            CV_ERROR (CV_StsBadSize, "sampleIdx array must be 1-dimensional");

        s_len = sampleIdx->rows + sampleIdx->cols - 1;
        s_step = sampleIdx->rows == 1 ?
                 1 : sampleIdx->step / CV_ELEM_SIZE(sampleIdx->type);

        s_type = CV_MAT_TYPE (sampleIdx->type);

        switch (s_type)
        {
        case CV_8UC1:
        case CV_8SC1:
        {
            uchar* s_data = sampleIdx->data.ptr;

            // sampleIdx is array of 1's and 0's -
            // i.e. it is a mask of the selected samples
            if( s_len != samples_all )
                CV_ERROR (CV_StsUnmatchedSizes,
                          "Sample mask should contain as many elements as the total number of samples");

            samples_selected = 0;
            for (i = 0; i < s_len; i++)
                samples_selected += s_data[i * s_step] != 0;

            if (samples_selected == 0)
                CV_ERROR (CV_StsOutOfRange, "No samples is selected!");
        }
        s_len = samples_selected;
        break;
        case CV_32SC1:
            if (s_len > samples_all)
                CV_ERROR (CV_StsOutOfRange,
//.........这里部分代码省略.........

CV_IMPL void
cvFloodFill( CvArr* arr, CvPoint seed_point,
             CvScalar newVal, CvScalar lo_diff, CvScalar up_diff,
             CvConnectedComp* comp, int flags, CvArr* maskarr )
{
    cv::Ptr<CvMat> tempMask;
    std::vector<CvFFillSegment> buffer;

    if( comp )
        memset( comp, 0, sizeof(*comp) );

    int i, type, depth, cn, is_simple;
    int buffer_size, connectivity = flags & 255;
    union {
        uchar b[4];
        int i[4];
        float f[4];
        double _[4];
    } nv_buf;
    nv_buf._[0] = nv_buf._[1] = nv_buf._[2] = nv_buf._[3] = 0;

    struct { cv::Vec3b b; cv::Vec3i i; cv::Vec3f f; } ld_buf, ud_buf;
    CvMat stub, *img = cvGetMat(arr, &stub);
    CvMat maskstub, *mask = (CvMat*)maskarr;
    CvSize size;

    type = CV_MAT_TYPE( img->type );
    depth = CV_MAT_DEPTH(type);
    cn = CV_MAT_CN(type);

    if( connectivity == 0 )
        connectivity = 4;
    else if( connectivity != 4 && connectivity != 8 )
        CV_Error( CV_StsBadFlag, "Connectivity must be 4, 0(=4) or 8" );

    is_simple = mask == 0 && (flags & CV_FLOODFILL_MASK_ONLY) == 0;

    for( i = 0; i < cn; i++ )
    {
        if( lo_diff.val[i] < 0 || up_diff.val[i] < 0 )
            CV_Error( CV_StsBadArg, "lo_diff and up_diff must be non-negative" );
        is_simple &= fabs(lo_diff.val[i]) < DBL_EPSILON && fabs(up_diff.val[i]) < DBL_EPSILON;
    }

    size = cvGetMatSize( img );

    if( (unsigned)seed_point.x >= (unsigned)size.width ||
        (unsigned)seed_point.y >= (unsigned)size.height )
        CV_Error( CV_StsOutOfRange, "Seed point is outside of image" );

    cvScalarToRawData( &newVal, &nv_buf, type, 0 );
    buffer_size = MAX( size.width, size.height ) * 2;
    buffer.resize( buffer_size );

    if( is_simple )
    {
        int elem_size = CV_ELEM_SIZE(type);
        const uchar* seed_ptr = img->data.ptr + img->step*seed_point.y + elem_size*seed_point.x;

        for(i = 0; i < elem_size; i++)
            if (seed_ptr[i] != nv_buf.b[i])
                break;

        if (i != elem_size)
        {
            if( type == CV_8UC1 )
                icvFloodFill_CnIR(img->data.ptr, img->step, size, seed_point, nv_buf.b[0],
                                  comp, flags, &buffer);
            else if( type == CV_8UC3 )
                icvFloodFill_CnIR(img->data.ptr, img->step, size, seed_point, cv::Vec3b(nv_buf.b),
                                  comp, flags, &buffer);
            else if( type == CV_32SC1 )
                icvFloodFill_CnIR(img->data.ptr, img->step, size, seed_point, nv_buf.i[0],
                                  comp, flags, &buffer);
            else if( type == CV_32FC1 )
                icvFloodFill_CnIR(img->data.ptr, img->step, size, seed_point, nv_buf.f[0],
                                  comp, flags, &buffer);
            else if( type == CV_32SC3 )
                icvFloodFill_CnIR(img->data.ptr, img->step, size, seed_point, cv::Vec3i(nv_buf.i),
                                  comp, flags, &buffer);
            else if( type == CV_32FC3 )
                icvFloodFill_CnIR(img->data.ptr, img->step, size, seed_point, cv::Vec3f(nv_buf.f),
                                  comp, flags, &buffer);
            else
                CV_Error( CV_StsUnsupportedFormat, "" );
            return;
        }
    }

    if( !mask )
    {
        /* created mask will be 8-byte aligned */
        tempMask = cvCreateMat( size.height + 2, (size.width + 9) & -8, CV_8UC1 );
        mask = tempMask;
    }
    else
    {
        mask = cvGetMat( mask, &maskstub );
        if( !CV_IS_MASK_ARR( mask ))
            CV_Error( CV_StsBadMask, "" );
//.........这里部分代码省略.........

CV_IMPL void
cvPreCornerDetect( const void* srcarr, void* dstarr, int aperture_size )
{
    CvSepFilter dx_filter, dy_filter, d2x_filter, d2y_filter, dxy_filter;
    CvMat *Dx = 0, *Dy = 0, *D2x = 0, *D2y = 0, *Dxy = 0;
    CvMat *tempsrc = 0;

    int buf_size = 1 << 12;

    CV_FUNCNAME( "cvPreCornerDetect" );

    __BEGIN__;

    int i, j, y, dst_y = 0, max_dy, delta = 0;
    int temp_step = 0, d_step;
    uchar* shifted_ptr = 0;
    int depth, d_depth;
    int stage = CV_START;
    CvSobelFixedIPPFunc ipp_sobel_vert = 0, ipp_sobel_horiz = 0,
                        ipp_sobel_vert_second = 0, ipp_sobel_horiz_second = 0,
                        ipp_sobel_cross = 0;
    CvSize el_size, size, stripe_size;
    int aligned_width;
    CvPoint el_anchor;
    double factor;
    CvMat stub, *src = (CvMat*)srcarr;
    CvMat dststub, *dst = (CvMat*)dstarr;
    bool use_ipp = false;

    CV_CALL( src = cvGetMat( srcarr, &stub ));
    CV_CALL( dst = cvGetMat( dst, &dststub ));

    if( CV_MAT_TYPE(src->type) != CV_8UC1 && CV_MAT_TYPE(src->type) != CV_32FC1 ||
            CV_MAT_TYPE(dst->type) != CV_32FC1 )
        CV_ERROR( CV_StsUnsupportedFormat, "Input must be 8uC1 or 32fC1, output must be 32fC1" );

    if( !CV_ARE_SIZES_EQ( src, dst ))
        CV_ERROR( CV_StsUnmatchedSizes, "" );

    if( aperture_size == CV_SCHARR )
        CV_ERROR( CV_StsOutOfRange, "CV_SCHARR is not supported by this function" );

    if( aperture_size < 3 || aperture_size > 7 || !(aperture_size & 1) )
        CV_ERROR( CV_StsOutOfRange,
                  "Derivative filter aperture size must be 3, 5 or 7" );

    depth = CV_MAT_DEPTH(src->type);
    d_depth = depth == CV_8U ? CV_16S : CV_32F;

    size = cvGetMatSize(src);
    aligned_width = cvAlign(size.width, 4);

    el_size = cvSize( aperture_size, aperture_size );
    el_anchor = cvPoint( aperture_size/2, aperture_size/2 );

    if( aperture_size <= 5 && icvFilterSobelVert_8u16s_C1R_p )
    {
        if( depth == CV_8U )
        {
            ipp_sobel_vert = icvFilterSobelVert_8u16s_C1R_p;
            ipp_sobel_horiz = icvFilterSobelHoriz_8u16s_C1R_p;
            ipp_sobel_vert_second = icvFilterSobelVertSecond_8u16s_C1R_p;
            ipp_sobel_horiz_second = icvFilterSobelHorizSecond_8u16s_C1R_p;
            ipp_sobel_cross = icvFilterSobelCross_8u16s_C1R_p;
        }
        else if( depth == CV_32F )
        {
            ipp_sobel_vert = icvFilterSobelVert_32f_C1R_p;
            ipp_sobel_horiz = icvFilterSobelHoriz_32f_C1R_p;
            ipp_sobel_vert_second = icvFilterSobelVertSecond_32f_C1R_p;
            ipp_sobel_horiz_second = icvFilterSobelHorizSecond_32f_C1R_p;
            ipp_sobel_cross = icvFilterSobelCross_32f_C1R_p;
        }
    }

    if( ipp_sobel_vert && ipp_sobel_horiz && ipp_sobel_vert_second &&
            ipp_sobel_horiz_second && ipp_sobel_cross )
    {
        CV_CALL( tempsrc = icvIPPFilterInit( src, buf_size, el_size ));
        shifted_ptr = tempsrc->data.ptr + el_anchor.y*tempsrc->step +
                      el_anchor.x*CV_ELEM_SIZE(depth);
        temp_step = tempsrc->step ? tempsrc->step : CV_STUB_STEP;
        max_dy = tempsrc->rows - aperture_size + 1;
        use_ipp = true;
    }
    else
    {
        ipp_sobel_vert = ipp_sobel_horiz = 0;
        ipp_sobel_vert_second = ipp_sobel_horiz_second = ipp_sobel_cross = 0;
        dx_filter.init_deriv( size.width, depth, d_depth, 1, 0, aperture_size );
        dy_filter.init_deriv( size.width, depth, d_depth, 0, 1, aperture_size );
        d2x_filter.init_deriv( size.width, depth, d_depth, 2, 0, aperture_size );
        d2y_filter.init_deriv( size.width, depth, d_depth, 0, 2, aperture_size );
        dxy_filter.init_deriv( size.width, depth, d_depth, 1, 1, aperture_size );
        max_dy = buf_size / src->cols;
        max_dy = MAX( max_dy, aperture_size );
    }

    CV_CALL( Dx = cvCreateMat( max_dy, aligned_width, d_depth ));
    CV_CALL( Dy = cvCreateMat( max_dy, aligned_width, d_depth ));
//.........这里部分代码省略.........

static void
icvCornerEigenValsVecs( const CvMat* src, CvMat* eigenv, int block_size,
                        int aperture_size, int op_type, double k=0. )
{
    CvSepFilter dx_filter, dy_filter;
    CvBoxFilter blur_filter;
    CvMat *tempsrc = 0;
    CvMat *Dx = 0, *Dy = 0, *cov = 0;
    CvMat *sqrt_buf = 0;

    int buf_size = 1 << 12;

    CV_FUNCNAME( "icvCornerEigenValsVecs" );

    __BEGIN__;

    int i, j, y, dst_y = 0, max_dy, delta = 0;
    int aperture_size0 = aperture_size;
    int temp_step = 0, d_step;
    uchar* shifted_ptr = 0;
    int depth, d_depth;
    int stage = CV_START;
    CvSobelFixedIPPFunc ipp_sobel_vert = 0, ipp_sobel_horiz = 0;
    CvFilterFixedIPPFunc ipp_scharr_vert = 0, ipp_scharr_horiz = 0;
    CvSize el_size, size, stripe_size;
    int aligned_width;
    CvPoint el_anchor;
    double factorx, factory;
    bool use_ipp = false;

    if( block_size < 3 || !(block_size & 1) )
        CV_ERROR( CV_StsOutOfRange, "averaging window size must be an odd number >= 3" );

    if( aperture_size < 3 && aperture_size != CV_SCHARR || !(aperture_size & 1) )
        CV_ERROR( CV_StsOutOfRange,
                  "Derivative filter aperture size must be a positive odd number >=3 or CV_SCHARR" );

    depth = CV_MAT_DEPTH(src->type);
    d_depth = depth == CV_8U ? CV_16S : CV_32F;

    size = cvGetMatSize(src);
    aligned_width = cvAlign(size.width, 4);

    aperture_size = aperture_size == CV_SCHARR ? 3 : aperture_size;
    el_size = cvSize( aperture_size, aperture_size );
    el_anchor = cvPoint( aperture_size/2, aperture_size/2 );

    if( aperture_size <= 5 && icvFilterSobelVert_8u16s_C1R_p )
    {
        if( depth == CV_8U && aperture_size0 == CV_SCHARR )
        {
            ipp_scharr_vert = icvFilterScharrVert_8u16s_C1R_p;
            ipp_scharr_horiz = icvFilterScharrHoriz_8u16s_C1R_p;
        }
        else if( depth == CV_32F && aperture_size0 == CV_SCHARR )
        {
            ipp_scharr_vert = icvFilterScharrVert_32f_C1R_p;
            ipp_scharr_horiz = icvFilterScharrHoriz_32f_C1R_p;
        }
        else if( depth == CV_8U )
        {
            ipp_sobel_vert = icvFilterSobelVert_8u16s_C1R_p;
            ipp_sobel_horiz = icvFilterSobelHoriz_8u16s_C1R_p;
        }
        else if( depth == CV_32F )
        {
            ipp_sobel_vert = icvFilterSobelVert_32f_C1R_p;
            ipp_sobel_horiz = icvFilterSobelHoriz_32f_C1R_p;
        }
    }

    if( ipp_sobel_vert && ipp_sobel_horiz ||
            ipp_scharr_vert && ipp_scharr_horiz )
    {
        CV_CALL( tempsrc = icvIPPFilterInit( src, buf_size,
                                             cvSize(el_size.width,el_size.height + block_size)));
        shifted_ptr = tempsrc->data.ptr + el_anchor.y*tempsrc->step +
                      el_anchor.x*CV_ELEM_SIZE(depth);
        temp_step = tempsrc->step ? tempsrc->step : CV_STUB_STEP;
        max_dy = tempsrc->rows - aperture_size + 1;
        use_ipp = true;
    }
    else
    {
        ipp_sobel_vert = ipp_sobel_horiz = 0;
        ipp_scharr_vert = ipp_scharr_horiz = 0;

        CV_CALL( dx_filter.init_deriv( size.width, depth, d_depth, 1, 0, aperture_size0 ));
        CV_CALL( dy_filter.init_deriv( size.width, depth, d_depth, 0, 1, aperture_size0 ));
        max_dy = buf_size / src->cols;
        max_dy = MAX( max_dy, aperture_size + block_size );
    }

    CV_CALL( Dx = cvCreateMat( max_dy, aligned_width, d_depth ));
    CV_CALL( Dy = cvCreateMat( max_dy, aligned_width, d_depth ));
    CV_CALL( cov = cvCreateMat( max_dy + block_size + 1, size.width, CV_32FC3 ));
    CV_CALL( sqrt_buf = cvCreateMat( 2, size.width, CV_32F ));
    Dx->cols = Dy->cols = size.width;

    if( !use_ipp )
//.........这里部分代码省略.........

CV_IMPL  CvBox2D
cvMinAreaRect2( const CvArr* array, CvMemStorage* storage )
{
    CvMemStorage* temp_storage = 0;
    CvBox2D box;
    CvPoint2D32f* points = 0;
    
    CV_FUNCNAME( "cvMinAreaRect2" );

    memset(&box, 0, sizeof(box));

    __BEGIN__;

    int i, n;
    CvSeqReader reader;
    CvContour contour_header;
    CvSeqBlock block;
    CvSeq* ptseq = (CvSeq*)array;
    CvPoint2D32f out[3];

    if( CV_IS_SEQ(ptseq) )
    {
        if( !CV_IS_SEQ_POINT_SET(ptseq) &&
            (CV_SEQ_KIND(ptseq) != CV_SEQ_KIND_CURVE || !CV_IS_SEQ_CONVEX(ptseq) ||
            CV_SEQ_ELTYPE(ptseq) != CV_SEQ_ELTYPE_PPOINT ))
            CV_ERROR( CV_StsUnsupportedFormat,
                "Input sequence must consist of 2d points or pointers to 2d points" );
        if( !storage )
            storage = ptseq->storage;
    }
    else
    {
        CV_CALL( ptseq = cvPointSeqFromMat(
            CV_SEQ_KIND_GENERIC, array, &contour_header, &block ));
    }

    if( storage )
    {
        CV_CALL( temp_storage = cvCreateChildMemStorage( storage ));
    }
    else
    {
        CV_CALL( temp_storage = cvCreateMemStorage(1 << 10));
    }

    if( !CV_IS_SEQ_CONVEX( ptseq ))
    {
        CV_CALL( ptseq = cvConvexHull2( ptseq, temp_storage, CV_CLOCKWISE, 1 ));
    }
    else if( !CV_IS_SEQ_POINT_SET( ptseq ))
    {
        CvSeqWriter writer;
        
        if( !CV_IS_SEQ(ptseq->v_prev) || !CV_IS_SEQ_POINT_SET(ptseq->v_prev))
            CV_ERROR( CV_StsBadArg,
            "Convex hull must have valid pointer to point sequence stored in v_prev" );
        cvStartReadSeq( ptseq, &reader );
        cvStartWriteSeq( CV_SEQ_KIND_CURVE|CV_SEQ_FLAG_CONVEX|CV_SEQ_ELTYPE(ptseq->v_prev),
                         sizeof(CvContour), CV_ELEM_SIZE(ptseq->v_prev->flags),
                         temp_storage, &writer );
            
        for( i = 0; i < ptseq->total; i++ )
        {
            CvPoint pt = **(CvPoint**)(reader.ptr);
            CV_WRITE_SEQ_ELEM( pt, writer );
        }

        ptseq = cvEndWriteSeq( &writer );
    }

    n = ptseq->total;

    CV_CALL( points = (CvPoint2D32f*)cvAlloc( n*sizeof(points[0]) ));
    cvStartReadSeq( ptseq, &reader );

    if( CV_SEQ_ELTYPE( ptseq ) == CV_32SC2 )
    {
        for( i = 0; i < n; i++ )
        {
            CvPoint pt;
            CV_READ_SEQ_ELEM( pt, reader );
            points[i].x = (float)pt.x;
            points[i].y = (float)pt.y;
        }
    }
    else
    {
        for( i = 0; i < n; i++ )
        {
            CV_READ_SEQ_ELEM( points[i], reader );
        }
    }
    
    if( n > 2 )
    {
        icvRotatingCalipers( points, n, CV_CALIPERS_MINAREARECT, (float*)out );
        box.center.x = out[0].x + (out[1].x + out[2].x)*0.5f;
        box.center.y = out[0].y + (out[1].y + out[2].y)*0.5f;
        box.size.height = (float)sqrt((double)out[1].x*out[1].x + (double)out[1].y*out[1].y);
        box.size.width = (float)sqrt((double)out[2].x*out[2].x + (double)out[2].y*out[2].y);
//.........这里部分代码省略.........

void crossCorr( const Mat& img, const Mat& _templ, Mat& corr,
                Size corrsize, int ctype,
                Point anchor, double delta, int borderType )
{
    const double blockScale = 4.5;
    const int minBlockSize = 256;
    std::vector<uchar> buf;

    Mat templ = _templ;
    int depth = img.depth(), cn = img.channels();
    int tdepth = templ.depth(), tcn = templ.channels();
    int cdepth = CV_MAT_DEPTH(ctype), ccn = CV_MAT_CN(ctype);

    CV_Assert( img.dims <= 2 && templ.dims <= 2 && corr.dims <= 2 );

    if( depth != tdepth && tdepth != std::max(CV_32F, depth) )
    {
        _templ.convertTo(templ, std::max(CV_32F, depth));
        tdepth = templ.depth();
    }

    CV_Assert( depth == tdepth || tdepth == CV_32F);
    CV_Assert( corrsize.height <= img.rows + templ.rows - 1 &&
               corrsize.width <= img.cols + templ.cols - 1 );

    CV_Assert( ccn == 1 || delta == 0 );

    corr.create(corrsize, ctype);

    int maxDepth = depth > CV_8S ? CV_64F : std::max(std::max(CV_32F, tdepth), cdepth);
    Size blocksize, dftsize;

    blocksize.width = cvRound(templ.cols*blockScale);
    blocksize.width = std::max( blocksize.width, minBlockSize - templ.cols + 1 );
    blocksize.width = std::min( blocksize.width, corr.cols );
    blocksize.height = cvRound(templ.rows*blockScale);
    blocksize.height = std::max( blocksize.height, minBlockSize - templ.rows + 1 );
    blocksize.height = std::min( blocksize.height, corr.rows );

    dftsize.width = std::max(getOptimalDFTSize(blocksize.width + templ.cols - 1), 2);
    dftsize.height = getOptimalDFTSize(blocksize.height + templ.rows - 1);
    if( dftsize.width <= 0 || dftsize.height <= 0 )
        CV_Error( CV_StsOutOfRange, "the input arrays are too big" );

    // recompute block size
    blocksize.width = dftsize.width - templ.cols + 1;
    blocksize.width = MIN( blocksize.width, corr.cols );
    blocksize.height = dftsize.height - templ.rows + 1;
    blocksize.height = MIN( blocksize.height, corr.rows );

    Mat dftTempl( dftsize.height*tcn, dftsize.width, maxDepth );
    Mat dftImg( dftsize, maxDepth );

    int i, k, bufSize = 0;
    if( tcn > 1 && tdepth != maxDepth )
        bufSize = templ.cols*templ.rows*CV_ELEM_SIZE(tdepth);

    if( cn > 1 && depth != maxDepth )
        bufSize = std::max( bufSize, (blocksize.width + templ.cols - 1)*
            (blocksize.height + templ.rows - 1)*CV_ELEM_SIZE(depth));

    if( (ccn > 1 || cn > 1) && cdepth != maxDepth )
        bufSize = std::max( bufSize, blocksize.width*blocksize.height*CV_ELEM_SIZE(cdepth));

    buf.resize(bufSize);

    // compute DFT of each template plane
    for( k = 0; k < tcn; k++ )
    {
        int yofs = k*dftsize.height;
        Mat src = templ;
        Mat dst(dftTempl, Rect(0, yofs, dftsize.width, dftsize.height));
        Mat dst1(dftTempl, Rect(0, yofs, templ.cols, templ.rows));

        if( tcn > 1 )
        {
            src = tdepth == maxDepth ? dst1 : Mat(templ.size(), tdepth, &buf[0]);
            int pairs[] = {k, 0};
            mixChannels(&templ, 1, &src, 1, pairs, 1);
        }

        if( dst1.data != src.data )
            src.convertTo(dst1, dst1.depth());

        if( dst.cols > templ.cols )
        {
            Mat part(dst, Range(0, templ.rows), Range(templ.cols, dst.cols));
            part = Scalar::all(0);
        }
        dft(dst, dst, 0, templ.rows);
    }

    int tileCountX = (corr.cols + blocksize.width - 1)/blocksize.width;
    int tileCountY = (corr.rows + blocksize.height - 1)/blocksize.height;
    int tileCount = tileCountX * tileCountY;

    Size wholeSize = img.size();
    Point roiofs(0,0);
    Mat img0 = img;

//.........这里部分代码省略.........

//.........这里部分代码省略.........

    blocksize.width = cvRound(templ->cols*block_scale);
    blocksize.width = MAX( blocksize.width, min_block_size - templ->cols + 1 );
    blocksize.width = MIN( blocksize.width, corr->cols );
    blocksize.height = cvRound(templ->rows*block_scale);
    blocksize.height = MAX( blocksize.height, min_block_size - templ->rows + 1 );
    blocksize.height = MIN( blocksize.height, corr->rows );

    dftsize.width = cvGetOptimalDFTSize(blocksize.width + templ->cols - 1);
    if( dftsize.width == 1 )
        dftsize.width = 2;
    dftsize.height = cvGetOptimalDFTSize(blocksize.height + templ->rows - 1);
    if( dftsize.width <= 0 || dftsize.height <= 0 )
        CV_Error( CV_StsOutOfRange, "the input arrays are too big" );

    // recompute block size
    blocksize.width = dftsize.width - templ->cols + 1;
    blocksize.width = MIN( blocksize.width, corr->cols );
    blocksize.height = dftsize.height - templ->rows + 1;
    blocksize.height = MIN( blocksize.height, corr->rows );

    dft_templ = cvCreateMat( dftsize.height*templ_cn, dftsize.width, max_depth );

#ifdef USE_OPENMP
    num_threads = cvGetNumThreads();
#else
    num_threads = 1;
#endif

    for( k = 0; k < num_threads; k++ )
        dft_img[k] = cvCreateMat( dftsize.height, dftsize.width, max_depth );

    if( templ_cn > 1 && templ_depth != max_depth )
        buf_size = templ->cols*templ->rows*CV_ELEM_SIZE(templ_depth);

    if( cn > 1 && depth != max_depth )
        buf_size = MAX( buf_size, (blocksize.width + templ->cols - 1)*
            (blocksize.height + templ->rows - 1)*CV_ELEM_SIZE(depth));

    if( (corr_cn > 1 || cn > 1) && corr_depth != max_depth )
        buf_size = MAX( buf_size, blocksize.width*blocksize.height*CV_ELEM_SIZE(corr_depth));

    if( buf_size > 0 )
    {
        for( k = 0; k < num_threads; k++ )
            buf[k].resize(buf_size);
    }

    // compute DFT of each template plane
    for( k = 0; k < templ_cn; k++ )
    {
        CvMat dstub, *src, *dst, temp;
        CvMat* planes[] = { 0, 0, 0, 0 };
        int yofs = k*dftsize.height;

        src = templ;
        dst = cvGetSubRect( dft_templ, &dstub, cvRect(0,yofs,templ->cols,templ->rows));
    
        if( templ_cn > 1 )
        {
            planes[k] = templ_depth == max_depth ? dst :
                cvInitMatHeader( &temp, templ->rows, templ->cols, templ_depth, &buf[0][0] );
            cvSplit( templ, planes[0], planes[1], planes[2], planes[3] );
            src = planes[k];
            planes[k] = 0;
        }

void cv::Laplacian( InputArray _src, OutputArray _dst, int ddepth, int ksize,
                    double scale, double delta, int borderType )
{
    int stype = _src.type(), sdepth = CV_MAT_DEPTH(stype), cn = CV_MAT_CN(stype);
    if (ddepth < 0)
        ddepth = sdepth;
    _dst.create( _src.size(), CV_MAKETYPE(ddepth, cn) );

#ifdef HAVE_TEGRA_OPTIMIZATION
    if (scale == 1.0 && delta == 0)
    {
        Mat src = _src.getMat(), dst = _dst.getMat();
        if (ksize == 1 && tegra::laplace1(src, dst, borderType))
            return;
        if (ksize == 3 && tegra::laplace3(src, dst, borderType))
            return;
        if (ksize == 5 && tegra::laplace5(src, dst, borderType))
            return;
    }
#endif

    if( ksize == 1 || ksize == 3 )
    {
        float K[2][9] =
        {
            { 0, 1, 0, 1, -4, 1, 0, 1, 0 },
            { 2, 0, 2, 0, -8, 0, 2, 0, 2 }
        };
        Mat kernel(3, 3, CV_32F, K[ksize == 3]);
        if( scale != 1 )
            kernel *= scale;
        filter2D( _src, _dst, ddepth, kernel, Point(-1, -1), delta, borderType );
    }
    else
    {
        int ktype = std::max(CV_32F, std::max(ddepth, sdepth));
        int wdepth = sdepth == CV_8U && ksize <= 5 ? CV_16S : sdepth <= CV_32F ? CV_32F : CV_64F;
        int wtype = CV_MAKETYPE(wdepth, cn);
        Mat kd, ks;
        getSobelKernels( kd, ks, 2, 0, ksize, false, ktype );

        CV_OCL_RUN(_dst.isUMat(),
                   ocl_Laplacian5(_src, _dst, kd, ks, scale,
                                  delta, borderType, wdepth, ddepth))

        const size_t STRIPE_SIZE = 1 << 14;
        Ptr<FilterEngine> fx = createSeparableLinearFilter(stype,
            wtype, kd, ks, Point(-1,-1), 0, borderType, borderType, Scalar() );
        Ptr<FilterEngine> fy = createSeparableLinearFilter(stype,
            wtype, ks, kd, Point(-1,-1), 0, borderType, borderType, Scalar() );

        Mat src = _src.getMat(), dst = _dst.getMat();
        int y