濃度投影

下図の２値画像を２値ブローブ解析して得られたリージョンにより処理対象画像の輝度統計を算出する処理です。

【処理対象】	【２値画像】

【リージョン】

処理時間:

    0.118 msec : FVCL.Blob.CFvBlob
    0.036 msec : FVCL.Blob.GetList
    0.013 msec : FVCL.Blob.GetSortList
    0.210 msec : FVCL.Measure.CFvProjection.Execute

サンプルコード:

//  $Revision: 1.3 $
void Projection2()
{
#ifdef _UNICODE
    typedef std::wstring    _TSTRING;
#else
    typedef std::string     _TSTRING;
#endif

    FVCL::Data::CFvImage    src(_T("./key_UC8_M.png"));
    FVCL::Data::CFvImage    bin(_T("./key_BIN_M.png"));
    FVCL::CFvTimeCounter    watch;
    double                  msec;
    std::map<_TSTRING, double>  times;

    // --------------------------------------------------
    // ２値ブローブ解析.
    FVCL::Blob::CFvBlobResult   result;
    {
        watch.Start();
        FVCL::Blob::CFvBlob         parser(&bin, &result);
        FVCL::Blob::CFvBlobParam&   param = parser.GetParam();
        param.SetColorMode( FVCL::Blob::ObjectColor::WhiteFG );
        parser.Execute();
        msec = watch.Stop();
        times[_T("FVCL.Blob.CFvBlob")] = msec;
    }

    // --------------------------------------------------
    // ２値ブローブ解析結果のフィルタリングとソート.
    FHANDLE                 hresult = result.GetHandle();
    FVCL::Blob::CFvBlobData data(hresult, 0);
    FVCL::CFvBuffer<UINT>   blob_numbers;
    {
        watch.Start();
        FVCL::CFvArray<FVCL::Blob::CFvBlobFilterRange> filters;
        filters.resize(1);
        filters[0].SetType(FVCL::Blob::FeatureType::AREA);
        filters[0].SetMin(100);
        filters[0].SetMax(FVCL::TypeRange::INT::Upper);
        FVCL::Blob::GetList(hresult, filters, &blob_numbers);
        msec = watch.Stop();
        times[_T("FVCL.Blob.GetList")] = msec;
    }
    {
        watch.Start();
        FVCL::Blob::GetSortList(hresult, FVCL::Blob::FeatureType::RECT1AREA, 1, &blob_numbers);
        msec = watch.Stop();
        times[_T("FVCL.Blob.GetSortList")] = msec;
    }

    // --------------------------------------------------
    // 計測.
    {
        FVCL::Measure::CFvProjectionResult  result_x;
        FVCL::Measure::CFvProjection        parser( &src, 0, FVCL::Measure::Direction::X, &result_x );
        FVCL::Data::CFvRegion               region;

        watch.Start();
        {
            data.SetBlobNo( blob_numbers[0] );
            data.GetRegion(&region);
            parser.Execute( region, FVCL::OriginMode::Image, FVCL::Measure::FeatureType::Rect2, 0.0 );
        }
        msec = watch.Stop();
        times[_T("FVCL.Measure.CFvProjection.Execute")] = msec;

        _tprintf(_T("%-5s,%5s,%9s,%9s,%9s,%9s,%9s,%9s\n"),
            _T("No."), _T("Count"), _T("Sum"), _T("Mean"), _T("Min"), _T("Max"), _T("Sigma"), _T("Var"));
        for(UINT i=0 ; i<result_x.GetCount() ; i++)
        {
            FVCL::Statistics& stat = result_x[i];
            _tprintf(_T("[%03d] %5d,%9.0f,%9.3f,%9.3f,%9.3f,%9.3f,%9.3f\n"),
                i, stat.Count, stat.Sum, stat.Mean, stat.Min, stat.Max, stat.Sigma, stat.Variance);
        }
    }

    // --------------------------------------------------
    _tprintf(_T("\n"));
    for(std::map<_TSTRING, double>::iterator iter = times.begin() ; iter != times.end() ; iter++)
    {
        _tprintf(_T("%9.3f msec : %s\n"), iter->second, iter->first.c_str());
    }
}