W0Dz,(=)I   $ C  ! 0/!i +N2n++*O-3 :.oD DGWX+a#k)kolo. 't3q )PD4444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444488888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888kmaxabsdifcdcenkroutine:Max_AbsDif_Cen:Matching:Chessboard Distance:$MATCHING/objects/kroutine/kmaxabsdifcdcen/uis/kmaxabsdifcdcen.pane::YES:Calcule absolute difference between two images and find the maximum (norm. by central value)ksabsdifcbsumkroutine:Sum_AbsDif_Sum:Matching:CityBlock Distance:$MATCHING/objects/kroutine/ksabsdifcbsum/uis/ksabsdifcbsum.pane::YES:Sum of Obsolute Differences (norm. by sum)e)ksmincbmeankroutine:Sum_Min_Mean:Matching:CityBlock Distance:$MATCHING/objects/kroutine/ksmincbmean/uis/ksmincbmean.pane::YES:Sum of Minima Normalized by Mean (City Block Distance)ksabsdifcbmedkroutine:Sum_AbsDif_Med:Matching:CityBlock Distance:$MATCHING/objects/kroutine/ksabsdifcbmed/uis/ksabsdifcbmed.pane::YES:Sum of Obsolute Differences (norm. by median)ksmincbsumkroutine:Sum_Min_Sum:Matching:CityBlock Distance:$MATCHING/objects/kroutine/ksmincbsum/uis/ksmincbsum.pane::YES:Sum of Minima Normalized by Sum (City Block Distance)kminQ G -Rkuns\-kssu='n\kusuklgmaxkroutine:Global_Max:Matching:Tools:$MATCHING/objects/kroutine/klgmax/uis/klgmax.pane::YES:Search for global maximum and generate a binary image and reportistance)kghmtkroutine:Ghmt:Matching:Others:$MATCHING/objects/kroutine/kghmt/uis/kghmt.pane::YES:Sum of an Erosion and an Anti-Dilationa (City Block Distance)kghmtkroutine:Ghmt:Matching:Others:$MATCHING/objects/kroutine/kghmt/uis/kghmt.pane::YES:Grayscale Hit-or-Miss Transforme::YES:Sum of Sup Generators (City Block Distance)ksmincbkroutine:Sum_Min:Matching:CityBlock Distance:$MATCHING/objects/kroutine/ksmincb/uis/ksmincb.pane::YES:Sum of Minima (City Block Distance)dean Distance)ksprodedkroutine:Sum_Products:Matching:Euclidean Distance:$MATCHING/objects/kroutine/ksproded/uis/ksproded.pane::YES:Correlation Coefficient Normalized)mber of Satisfied Conditions)kssupgennckroutine:Sum_SupGen:Matching:Number of Conditions:$MATCHING/objects/kroutine/kssupgennc/uis/kssupgennc.pane::YES:Sum of Sup Generators (Number of Satisfied Conditions)kghmtmedkroutine:Ghmt_Med:Matching:Others:$MATCHING/objects/kroutine/kghmtmed/uis/kghmtmed.pane::YES:Grayscale Hit-or-Miss Transform (norm. by median)ock Distance)kreportkroutine:Report:Matching:Tools:$MATCHING/objects/kroutine/kreport/uis/kreport.pane::YES:Generate report with the locations of same value in an image Distance)f Not_Satisfied Conditionsksprodedmedkroutine:Sum_Products_Med:Matching:Euclidean Distance:$MATCHING/objects/kroutine/ksprodedmed/uis/ksprodedmed.pane::YES:Sum of Products (Euclidean Distance norm. by median)Conditions)ksprodedmeankroutine:Sum_Products_Mean:Matching:Euclidean Distance:$MATCHING/objects/kroutine/ksprodedmean/uis/ksprodedmean.pane::YES:Sum of Products (Euclidean Distance norm. by Mean)Distance)kcorrel_medkroutine:kcorrel_med:Matching:Euclidean Distance:$MATCHING/objects/kroutine/kcorrel_med/uis/kcorrel_med.pane::YES:Correlation Coefficient Normalized by Median. by Centre Value)nditions)klgminkroutine:Global_Min:Matching:Tools:$MATCHING/objects/kroutine/klgmin/uis/klgmin.pane::YES:Search for global minimum and generate a binary image and reportalized by median) (Number of Conditions)ksupgenkroutine:SupGen:Matching:Others:$MATCHING/objects/kroutine/ksupgen/uis/ksupgen.pane::YES:Sup Generatorkinfgenkroutine:InfGen:Matching:Others:$MATCHING/objects/kroutine/kinfgen/uis/kinfgen.pane::YES:Inf Generatorkusupgencdmeankroutine:U_SupGen_Mean:Matching:Chessboard Distance:$MATCHING/objects/kroutine/kusupgencdmean/uis/kusupgencdmean.pane::YES:Chessboard Distance normalized by meankreport1kroutine:Report1:Matching:Tools:$MATCHING/objects/kroutine/kreport1/uis/kreport1.pane::YES:Reportilarity measure based on the L1 norm Distance normalized by medianksmincbmedkroutine:Sum_Min_Med:Matching:CityBlock Distance:$MATCHING/objects/kroutine/ksmincbmed/uis/ksmincbmed.pane::YES:Sum of Minima Normalized by Mediankgcbmedkroutine:G_L1_Norm_Med:Matching:CityBlock Distance:$MATCHING/objects/kroutine/kgcbmed/uis/kgcbmed.pane::YES:Similarity measure based on the L1 norm (normalized by median)diankssupgenncmedkroutine:Sum_SupGen_Med:Matching:Number of Conditions:$MATCHING/objects/kroutine/kssupgenncmed/uis/kssupgenncmed.pane::YES:Sum of Sup Generators Normalized by Mediankteste1kroutine:Teste1:Matching:Chessboard Distance:$MATCHING/objects/kroutine/kteste1/uis/kteste1.pane::YES:t-or-Miss Transform (norm. by central value)d by Medianknnsckroutine:Number_NS_Cond:Matching:Number of Conditions:$MATCHING/objects/kroutine/knnsc/uis/knnsc.pane::YES:Analyse and count if pixel value not belongs to an intervaltervalknnscmeankroutine:Number_NS_Cond_Mean:Matching:Number of Conditions:$MATCHING/objects/kroutine/knnscmean/uis/knnscmean.pane::YES:Analyse and count if pixel value not belongs to an interval(norm. by mean)knnscmedkroutine:Number_NS_Cond_Med:Matching:Number of Conditions:$MATCHING/objects/kroutine/knnscmed/uis/knnscmed.pane::YES:Analyse and count if pixel value not belongs to an interval(norm. by med)kssupgenncmeankroutine:Sum_SupGen_Mean:Matching:Number of Conditions:$MATCHING/objects/kroutine/kssupgenncmean/uis/kssupgenncmean.pane::YES:Analyse and count if pixel value belongs to an interval(norm. by mean)an)ksmincbcenkroutine:Sum_Min_Cen:Matching:CityBlock Distance:$MATCHING/objects/kroutine/ksmincbcen/uis/ksmincbcen.pane::YES:Sum of Minima Normalized by Centre Valueklgmaxrelkroutine:GMax_Rel:Matching:Tools:$MATCHING/objects/kroutine/klgmaxrel/uis/klgmaxrel.pane::YES:Search for global maximum and generate a reportimage and reportzed by Centre Valuekssupgennccenkroutine:Sum_SupGen_Cen:Matching:Number of Conditions:$MATCHING/objects/kroutine/kssupgennccen/uis/kssupgennccen.pane::YES:Sum of Sup Generators Normalized by Centre Valuekcorrel_meankroutine:kcorrel_mean:Matching:Euclidean Distance:$MATCHING/objects/kroutine/kcorrel_mean/uis/kcorrel_mean.pane::YES:Correlation Coefficient Normalized by Meanby mean)val (Norm. by Centre Value)kmaxminkroutine:Max_Min:Matching:Others:$MATCHING/objects/kroutine/kmaxmin/uis/kmaxmin.pane::YES:Compare two images and find the max min between themminimum between themkmaxminsumkroutine:Max_Min_Sum:Matching:Others:$MATCHING/objects/kroutine/kmaxminsum/uis/kmaxminsum.pane::YES:Compare two images and find the max min between them (norm. by sum)kmaxminmeankroutine:Max_Min_Mean:Matching:Others:$MATCHING/objects/kroutine/kmaxminmean/uis/kmaxminmean.pane::YES:Compare two images and find the max min between them (norm. by mean)kmaxminmedkroutine:Max_Min_Med:Matching:Others:$MATCHING/objects/kroutine/kmaxminmed/uis/kmaxminmed.pane::YES:Compare two images and find the max min between them (norm. by median)klcbmeankroutine:L_L1_Norm_Mean:Matching:CityBlock Distance:$MATCHING/objects/kroutine/klcbmean/uis/klcbmean.pane::YES:Similarity measure based on L1 norm (normalized by mean)tre value)kminmaxsumkroutine:Min_Max_Sum:Matching:Others:$MATCHING/objects/kroutine/kminmaxsum/uis/kminmaxsum.pane::YES:Compare two images and find the min max between them (norm. by sum)kminmaxkroutine:Min_Max:Matching:Others:$MATCHING/objects/kroutine/kminmax/uis/kminmax.pane::YES:Compare two images and find the min max between themkminmaxmeankroutine:Min_Max_Mean:Matching:Others:$MATCHING/objects/kroutine/kminmaxmean/uis/kminmaxmean.pane::YES:Compare two images and find the min max between them (nomr. by mean)kminmaxmedkroutine:Min_Max_Med:Matching:Others:$MATCHING/objects/kroutine/kminmaxmed/uis/kminmaxmed.pane::YES:Compare two images and find the min max between them (nomr. by median)klcbcenkroutine:L_L1_Norm_Cen:Matching:CityBlock Distance:$MATCHING/objects/kroutine/klcbcen/uis/klcbcen.pane::YES:Similarity measure based on L1 norm (normalized by central value)alue)kunsumkroutine:Union_Sum:Matching:Others:$MATCHING/objects/kroutine/kunsum/uis/kunsum.pane::YES:Sum two images and search for maximum value imageklminkroutine:Global_Min:Matching:Tools:$MATCHING/objects/kroutine/klmin/uis/klmin.pane::YES:Search for global minimum and generate a binary imagektestekroutine:Teste:Matching:Chessboard Distance:$MATCHING/objects/kroutine/kteste/uis/kteste.pane::YES: global maxima and generate a binary imagekgeoutmkroutine:Geo_Utm:Matching:Tools:$MATCHING/objects/kroutine/kgeoutm/uis/kgeoutm.pane::YES:GEO -> UTMglobal minimum and generate a binary imageklgmaxkroutine:Global_Max:Matching:Tools:$MATCHING/objects/kroutine/klgmax/uis/klgmax.pane::YES:Search for global maximum and generate a binary imagekghmtcenkroutine:Ghmt_Cen:Matching:Others:$MATCHING/objects/kroutine/kghmtcen/uis/kghmtcen.pane::YES:Grayscale Hit-or-Miss Transform (norm. by central value)kunsumcenkroutine:Union_Sum_Cen:Matching:Others:$MATCHING/objects/kroutine/kunsumcen/uis/kunsumcen.pane::YES:Sum two images and search for maximum value (norm. by central value)kunsummeankroutine:Union_Sum_Mean:Matching:Others:$MATCHING/objects/kroutine/kunsummean/uis/kunsummean.pane::YES:Sum two images and search for maximum value (norm. by mean)kteste2kroutine:Teste2:Matching:Chessboard Distance:$MATCHING/objects/kroutine/kteste2/uis/kteste2.pane::YES:um two images and search for maximum value (norm. by med)kunsummedkroutine:Union_Sum_Med:Matching:Others:$MATCHING/objects/kroutine/kunsummed/uis/kunsummed.pane::YES:Sum two images and search for maximum value (norm. by median)kghmtmeankroutine:Ghmt_Mean:Matching:Others:$MATCHING/objects/kroutine/kghmtmean/uis/kghmtmean.pane::YES:Grayscale Hit-or-Miss Transform (norm. by mean)ksabsdifcbmeankroutine:Sum_AbsDif_Mean:Matching:CityBlock Distance:$MATCHING/objects/kroutine/ksabsdifcbmean/uis/ksabsdifcbmean.pane::YES:Sum of Obsolute Differences (norm. by mean) the maximumkmaxabsdifcdmedkroutine:Max_AbsDif_Med:Matching:Chessboard Distance:$MATCHING/objects/kroutine/kmaxabsdifcdmed/uis/kmaxabsdifcdmed.pane::YES:Calcule absolute difference between two images and find the maximum (norm. by median)kmaxabsdifcdkroutine:Max_AbsDif:Matching:Chessboard Distance:$MATCHING/objects/kroutine/kmaxabsdifcd/uis/kmaxabsdifcd.pane::YES:Calcule absolute difference between two images and find the maximum the maximum (norm. by med.)kmaxabsdifcdmeankroutine:Max_AbsDif_Mean:Matching:Chessboard Distance:$MATCHING/objects/kroutine/kmaxabsdifcdmean/uis/kmaxabsdifcdmean.pane::YES:Calcule absolute difference between two images and find the maximum (norm. by mean)#%+*\C++\kusu0QQ0ksab.h0kmax/3kssu#J(kunst@ksabӧkssuw -ksprBklcb| Dklgm] knns_ $klcbWi &kminM%okmin B8kmin2ja ,kghmT /Ukghm#(kgcb \kgl12V  ksmi?E ksmi>8 "1kmax#(K b\krep+l kcor=`knnsO ,kunskusu c 1kmax) klgmH>HI`kmaxs ksmi ksmi]E, Vksabw] HkcorkusuQ G -RkunsN~>kcor kgl1Nz kcor|A "kmax_y $kmin@ kmax_" .kunsw IkssuG'4ksab{8CV ikspr]&krepnܨ=kgcbs{ ksprf ksmiS4 &kmin] kghmknnsccenkroutine:Number_NS_Cond_Cen:Matching:Number of Conditions:$MATCHING/objects/kroutine/knnsccen/uis/knnsccen.pane::YES:Analyse and count if pixel value not belongs to an interval (Norm. by Central Value)kgcbmeankroutine:G_L1_Norm_Mean:Matching:CityBlock Distance:$MATCHING/objects/kroutine/kgcbmean/uis/kgcbmean.pane::YES:Similarity measure based on the L1 norm (normalized by mean)alue)kgcbcenkroutine:G_L1_Norm_Cen:Matching:CityBlock Distance:$MATCHING/objects/kroutine/kgcbcen/uis/kgcbcen.pane::YES:Similarity measure based on the L1 norm (normalized by central value)kcorrel_cenkroutine:kcorrel_cen:Matching:Euclidean Distance:$MATCHING/objects/kroutine/kcorrel_cen/uis/kcorrel_cen.pane::YES:Correlation Coefficient Normalized by Central Valuekcorrelkroutine:kcorrel:Matching:Euclidean Distance:$MATCHING/objects/kroutine/kcorrel/uis/kcorrel.pane::YES:Correlation Coefficientksabsdifcbcenkroutine:Sum_AbsDif_Cen:Matching:CityBlock Distance:$MATCHING/objects/kroutine/ksabsdifcbcen/uis/ksabsdifcbcen.pane::YES:Sum of Obsolute Differences (norm. by central value)ksprodedcenkroutine:Sum_Products_Cen:Matching:Euclidean Distance:$MATCHING/objects/kroutine/ksprodedcen/uis/ksprodedcen.pane::YES:Sum od Products (Euclidean Distance norm. by Central Value)kmaxmincenkroutine:Max_Min_Cen:Matching:Others:$MATCHING/objects/kroutine/kmaxmincen/uis/kmaxmincen.pane::YES:Compare two images and find the max min between them (norm. by central value)kminmaxcenkroutine:Min_Max_Cen:Matching:Others:$MATCHING/objects/kroutine/kminmaxcen/uis/kminmaxcen.pane::YES:Compare two images and find the min max between them (nomr. by central value)klcbmedkroutine:L_L1_Norm_Med:Matching:CityBlock Distance:$MATCHING/objects/kroutine/klcbmed/uis/klcbmed.pane::YES:Similarity measure based on L1 norm (normalized by median)