OpenCV beta 5中的cvAdaptiveThreshold源代码我粗略的看了一下,太简单.

算法就是先图象的平滑,均值减去param1 ,

static void
icvAdaptiveThreshold_MeanC( const CvMat* src, CvMat* dst, int method,
                            int maxValue, int type, int size, double delta )
{
    CvMat* mean = 0;
   
    CV_FUNCNAME( "icvAdaptiveThreshold_MeanC" );

    __BEGIN__;

    if( size <= 1 || (size&1) == 0 )
        CV_ERROR( CV_StsOutOfRange, "Neighborhood size must be >=3 and odd (3, 5, 7, ...)" );

    if( maxValue < 0 )
    {
        CV_CALL( cvSetZero( dst ));
        EXIT;
    }

    CV_CALL( mean=cvCreateMat( src->rows, src->cols, CV_8UC1 ));
    CV_CALL( cvSmooth( src, mean, method == CV_ADAPTIVE_THRESH_MEAN_C ?
                       CV_BLUR : CV_GAUSSIAN, size, size ));
    CV_CALL( cvSubS( mean, cvRealScalar( delta ), mean ));
    CV_CALL( cvCmp( src, mean, dst, type == CV_THRESH_BINARY ? CV_CMP_GT : CV_CMP_LT ));

    if( maxValue < 255 )
        CV_CALL( cvAndS( dst, cvScalarAll( maxValue ), dst ));

    __END__;

    cvReleaseMat( &mean );
}

CV_IMPL void
cvAdaptiveThreshold( const void *srcIm, void *dstIm, double maxValue,
                     int method, int type, int blockSize, double param1 )
{
    CvMat src_stub, dst_stub;
    CvMat *src = 0, *dst = 0;

    CV_FUNCNAME( "cvAdaptiveThreshold" );

    __BEGIN__;

    if( type != CV_THRESH_BINARY && type != CV_THRESH_BINARY_INV )
        CV_ERROR( CV_StsBadArg, "Only CV_TRESH_BINARY and CV_THRESH_BINARY_INV "
                                "threshold types are acceptable" );

    CV_CALL( src = cvGetMat( srcIm, &src_stub ));
    CV_CALL( dst = cvGetMat( dstIm, &dst_stub ));

    if( !CV_ARE_CNS_EQ( src, dst ))
        CV_ERROR( CV_StsUnmatchedFormats, "" );

    if( CV_MAT_TYPE(dst->type) != CV_8UC1 )
        CV_ERROR( CV_StsUnsupportedFormat, "" );

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

    switch( method )
    {
    case CV_ADAPTIVE_THRESH_MEAN_C:
    case CV_ADAPTIVE_THRESH_GAUSSIAN_C:
        CV_CALL( icvAdaptiveThreshold_MeanC( src, dst, method, cvRound(maxValue),type,
                                             blockSize, param1 ));
        break;
    default:
        CV_ERROR( CV_BADCOEF_ERR, "" );
    }

    __END__;
}