Halcon學(xué)習(xí)之六：獲取Image圖像中Region區(qū)域的特征參數(shù)

1、HYPERLINK /rocky69/article/details/7246935Halcon學(xué)習(xí)之六：獲取Image圖像中Region區(qū)域的特征參數(shù) area_center_gray ( Regions, Image : : : Area, Row, Column ) 計(jì)算Image圖像中Region區(qū)域的面積Area和重心（Row，Column）。cooc_feature_image ( Regions, Image : : LdGray, Direction : Energy,Correlation, Homogeneity, Contrast ) 計(jì)算共生矩陣和推導(dǎo)出灰度特征值 Di

2、rection：灰度共生矩陣計(jì)算的方向 Energy：灰度值能量 Correlation：灰度值的相互關(guān)系Homogeneity：灰度值的均勻性Contrast：灰度值的對比度cooc_feature_matrix ( CoocMatrix : : : Energy, Correlation,Homogeneity, Contrast )根據(jù)共生矩陣計(jì)算灰度特征值elliptic_axis_gray ( Regions, Image : : : Ra, Rb, Phi )計(jì)算Image圖像的Region區(qū)域的Ra，Rb和Phi。entropy_gray ( Regions, Image : :

3、 : Entropy, Anisotropy )Image圖像中Region區(qū)域的計(jì)算熵Entropy和各向異性Anisotropy。estimate_noise ( Image : : Method, Percent : Sigma )從單一圖像 Image中估計(jì)圖像的噪聲。Sigma：加性噪聲的標(biāo)準(zhǔn)偏差Method ：估計(jì)噪聲的方法Methodfoerstner、immerkaer、least_squares、mean、fit_surface_first_order ( Regions, Image : : Algorithm, Iterations,ClippingFactor : Al

4、pha, Beta, Gamma )計(jì)算一階灰度平面的灰度矩陣和灰度值的逼近參數(shù)。Algorithm：采用的算法Algorithm：迭代次數(shù)ClippingFactor：消除臨界值的削波系數(shù)fit_surface_second_order ( Regions, Image : : Algorithm, Iterations,ClippingFactor : Alpha, Beta, Gamma, Delta, Epsilon, Zeta )計(jì)算二階灰度平面的灰度矩陣和灰度值的逼近參數(shù)。fuzzy_entropy ( Regions, Image : : Apar, Cpar : Entropy

5、 )確定區(qū)域Regions的模糊熵 將圖像視為模糊集合Apar為模糊區(qū)域的起始點(diǎn)Cpar為模糊區(qū)域的結(jié)束點(diǎn)Entropy為Regions的模糊熵fuzzy_perimeter ( Regions, Image : : Apar, Cpar : Perimeter )計(jì)算Region區(qū)域的模糊周長gen_cooc_matrix ( Regions, Image : Matrix : LdGray, Direction : )生成Image圖像Region區(qū)域的共生矩陣gray_histo ( Regions, Image : : : AbsoluteHisto, RelativeHisto )獲

6、取Image圖像Region區(qū)域的灰度相對直方圖RelativeHisto和絕對直方圖AbsoluteHisto。注意：Region區(qū)域必須先計(jì)算過它的直方圖。gray_histo_abs ( Regions, Image : : Quantization : AbsoluteHisto )獲取Image圖像Region區(qū)域的灰度絕對直方圖AbsoluteHisto。Quantization：灰度值的量化、gray_projections ( Region, Image : : Mode : HorProjection,VertProjection )計(jì)算Region區(qū)域在水平方向和垂直方向的

7、灰度值投影。histo_2dim ( Regions, ImageCol, ImageRow : Histo2Dim : : )計(jì)算二通道灰度圖像的直方圖intensity ( Regions, Image : : : Mean, Deviation )計(jì)算region區(qū)域的灰度平均值和偏差min_max_gray ( Regions, Image : : Percent : Min, Max, Range )計(jì)算Region區(qū)域的最大最小灰度值。Range：最大灰度值和最小灰度值之間的差距moments_gray_plane ( Regions, Image : : : MRow, MCol

8、, Alpha, Beta,Mean )計(jì)算平面的灰度矩陣和灰度值的逼近參數(shù)。plane_deviation ( Regions, Image : : : Deviation )逼近的圖象平面計(jì)算灰度值偏差select_gray ( Regions, Image : SelectedRegions : Features, Operation,Min, Max : )根據(jù)灰度值選擇區(qū)域Featuresarea、row、column、ra、rb、phi、min、max、mean、deviation、plane_deviation、anisotropy、entropy、fuzzy_entropy、f

9、uzzy_perimeter、moments_row、moments_column、alpha、betaOperationand、orshape_histo_all ( Region, Image : : Feature : AbsoluteHisto,RelativeHisto )shape_histo_point ( Region, Image : : Feature, Row,Column : AbsoluteHisto, RelativeHisto )獲取閾值特征直方圖Featureconnected_components、convexity、compactness、anisometr

10、y、holes 程序：c-sharp HYPERLINK /xinrui_hhuc/article/details/6131394#view plainHYPERLINK /xinrui_hhuc/article/details/6131394#copyread_image (Image, G:/Halcon/機(jī)器視覺/images/bin_switch/bin_switch_3.png) regiongrowing (Image, Regions, 3, 3, 1, 500) area_center_gray (Regions, Image, Area, Row, Column) cooc_

11、feature_image (Regions, Image, 6, 0, Energy, Correlation, Homogeneity, Contrast) elliptic_axis_gray (Regions, Image, Ra, Rb, Phi) entropy_gray (Regions, Image, Entropy, Anisotropy) estimate_noise (Image, mean, 20, Sigma) fit_surface_first_order (Regions, Image, regression, 5, 2, Alpha, Beta, Gamma) fit_surface_second_order (Regions, Image, regression, 5, 2, Alpha1, Beta1, Gamma1, Delta, Epsilon, Zeta) fuzzy_entropy (Regions, Image, 0, 255, Entropy1) fuzzy_perimeter (Regions, Image, 0, 255, Perimeter) gen_cooc_mat