２値ブローブ解析

濃淡画像を２値化して、２値ブローブ解析し、２つのブローブの重心間の距離を計測する例です。

---

プレビュー:

２値ブローブ解析結果

２点間の距離

---

ワークフロー:

---

ソースコード:

namespace FVIL.Parser
{
    using System;
    using System.Collections.Generic;
    using System.Text;
    using System.Drawing;
    using System.Reflection;
    using System.ComponentModel;
    using System.Windows.Forms;
    using System.Runtime.Serialization;
    using System.Security.Permissions;
    using System.Globalization;
    using fvalgcli;
    
    [System.SerializableAttribute()]
    [System.ComponentModel.TypeConverterAttribute(typeof(System.ComponentModel.ExpandableObjectConverter))]
    public partial class ParserNodeUser : FVIL.Parser.ParserNodeUnit
    {
        public override void Execute(object sender, System.EventArgs e)
        {
            FVIL.Data.CFviImage target1_out0 = new FVIL.Data.CFviImage(320, 240, FVIL.ImageType.UC8, 1);
            FVIL.Data.CFviImage target2_out0 = new FVIL.Data.CFviImage(320, 240, FVIL.ImageType.BIN, 1);
            FVIL.Blob.CFviBlobList target3_out0 = new FVIL.Blob.CFviBlobList();
            FVIL.Blob.CFviBlobData target4_out0 = new FVIL.Blob.CFviBlobData();
            FVIL.Data.CFviPoint target4_out1 = new FVIL.Data.CFviPoint(59.94997843898232, 72.105648986632175);
            int target4_out2 = 82;
            int target4_out3 = 94;
            FVIL.Blob.CFviBlobData target5_out0 = new FVIL.Blob.CFviBlobData();
            FVIL.Data.CFviPoint target5_out1 = new FVIL.Data.CFviPoint(202.01071237279058, 181.78628816282807);
            int target5_out2 = 114;
            int target5_out3 = 55;
            double target6_out0 = 179.47449605977764;

            // 画像#1
            target1_out0 = ((FVIL.Parser.IDataObject<FVIL.Data.CFviImage>)(ParserInfo)).Infos[0].Data;

            // ２値化#1
            FVIL.Conversion.CFviBinarizeDiscrimination target2 = new FVIL.Conversion.CFviBinarizeDiscrimination();
            target2.SrcImages[0] = target1_out0;
            target2.DstImages[0] = target2_out0;
            target2.Execute();

            // ２値ブローブ解析#1
            FVIL.Blob.CFviBlob target3 = new FVIL.Blob.CFviBlob();
            target3.SrcImages[0] = target2_out0;
            target3.ContinueOption = FVIL.Blob.ContinueOption.None;
            target3.OriginMode = FVIL.OriginMode.Image;
            target3.Offset = new System.Drawing.Point(0, 0);
            target3.Param.KeepResultsAfterOverflow = false;
            target3.Param.PrecalcFeatures = FVIL.Blob.FeatureFlag.None;
            target3.Param.Neighborhood = FVIL.Blob.Neighborhood.Four;
            target3.Param.ColorMode = FVIL.Blob.ObjectColor.WhiteFG_BlackBG;
            target3.Param.MaxRows = 0;
            target3.Param.MaxBlobs = 0u;
            target3.Param.MaxRuns = 0u;
            target3.Execute();
            System.Collections.Generic.List<FVIL.Blob.CFviBlobFilterRange> target3_filters = 
                new System.Collections.Generic.List<FVIL.Blob.CFviBlobFilterRange>();
            target3_filters.Add(new FVIL.Blob.CFviBlobFilterRange(FVIL.Blob.FeatureType.RECT1AREA, 1000, 4294967295));
            target3_out0 = target3.Result.GetBlobList(target3_filters);

            // ブローブデータ#1
            target4_out0.CopyFrom(target3_out0[1]);
            target4_out1 = target4_out0.Center;
            target4_out2 = target4_out0.Xdiff;
            target4_out3 = target4_out0.Ydiff;

            // ブローブデータ#2
            target5_out0.CopyFrom(target3_out0[4]);
            target5_out1 = target5_out0.Center;
            target5_out2 = target5_out0.Xdiff;
            target5_out3 = target5_out0.Ydiff;

            // 距離(２点間)#1
            FVIL.Data.CFviPoint target6_points = new FVIL.Data.CFviPoint[2];
            target6_points.Add(target5_out1);
            target6_points.Add(target4_out1);
            target6_out0 = FVIL.Caliper.Function.Distance(target6_points);
        }
    }
}