Halcon学习之六:获取Image图像中Region区域的特征参数
area_center_gray?(?Regions,?Image?:?:?:?Area,?Row,?Column?)?? ?計算Image圖像中Region區域的面積Area和重心(Row,Column)。
cooc_feature_image?(?Regions,?Image?:?:?LdGray,?Direction?:?Energy,Correlation,?Homogeneity,?Contrast?)? ?計算共生矩陣和推導出灰度特征值
???Direction:灰度共生矩陣計算的方向?? ?Energy:灰度值能量 ?? ?Correlation:灰度值的相互關系?Homogeneity:灰度值的均勻性?Contrast:灰度值的對比度
cooc_feature_matrix?(?CoocMatrix?:?:?:?Energy,?Correlation,Homogeneity,?Contrast?)?根據共生矩陣計算灰度特征值
elliptic_axis_gray?(?Regions,?Image?:?:?:?Ra,?Rb,?Phi?)?計算Image圖像的Region區域的Ra,Rb和Phi。
entropy_gray?(?Regions,?Image?:?:?:?Entropy,?Anisotropy?)?Image圖像中Region區域的計算熵Entropy和各向異性Anisotropy。
estimate_noise?(?Image?:?:?Method,?Percent?:?Sigma?)?從單一圖像?Image中估計圖像的噪聲。
Sigma:加性噪聲的標準偏差?Method?:估計噪聲的方法?Method∈{foerstner、immerkaer、least_squares、mean}、
fit_surface_first_order?(?Regions,?Image?:?:?Algorithm,?Iterations,?ClippingFactor?:?Alpha,?Beta,?Gamma?)?計算一階灰度平面的灰度矩陣和灰度值的逼近參數。
Algorithm:采用的算法?Algorithm:迭代次數?ClippingFactor:消除臨界值的削波系數
fit_surface_second_order?(?Regions,?Image?:?:?Algorithm,?Iterations,?ClippingFactor?:?Alpha,?Beta,?Gamma,?Delta,?Epsilon,?Zeta?)?計算二階灰度平面的灰度矩陣和灰度值的逼近參數。
fuzzy_entropy?(?Regions,?Image?:?:?Apar,?Cpar?:?Entropy?)?確定區域Regions的模糊熵?將圖像視為模糊集合?Apar為模糊區域的起始點?Cpar為模糊區域的結束點?Entropy為Regions的模糊熵
fuzzy_perimeter?(?Regions,?Image?:?:?Apar,?Cpar?:?Perimeter?)?計算Region區域的模糊周長
gen_cooc_matrix?(?Regions,?Image?:?Matrix?:?LdGray,?Direction?:?)?生成Image圖像Region區域的共生矩陣
gray_histo?(?Regions,?Image?:?:?:?AbsoluteHisto,?RelativeHisto?)?獲取Image圖像Region區域的灰度相對直方圖RelativeHisto和絕對直方圖AbsoluteHisto。?注意:Region區域必須先計算過它的直方圖。
gray_histo_abs?(?Regions,?Image?:?:?Quantization?:?AbsoluteHisto?)?獲取Image圖像Region區域的灰度絕對直方圖AbsoluteHisto。?Quantization:灰度值的量化、
gray_projections?(?Region,?Image?:?:?Mode?:?HorProjection,?VertProjection?)?計算Region區域在水平方向和垂直方向的灰度值投影。
histo_2dim?(?Regions,?ImageCol,?ImageRow?:?Histo2Dim?:?:?)?計算二通道灰度圖像的直方圖
intensity?(?Regions,?Image?:?:?:?Mean,?Deviation?)?計算region區域的灰度平均值和偏差
min_max_gray?(?Regions,?Image?:?:?Percent?:?Min,?Max,?Range?)?計算Region區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,?Alpha,?Beta,Mean?)?計算平面的灰度矩陣和灰度值的逼近參數。
plane_deviation?(?Regions,?Image?:?:?:?Deviation?)?逼近的圖象平面計算灰度值偏差?
select_gray?(?Regions,?Image?:?SelectedRegions?:?Features,?Operation,Min,?Max?:?)
根據灰度值選擇區域
Features∈{area、row、column、ra、rb、phi、min、max、mean、deviation、plane_deviation、anisotropy、entropy、fuzzy_entropy、fuzzy_perimeter、moments_row、moments_column、alpha、beta}
Operation∈{and、or}
shape_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
Feature∈{connected_components、convexity、compactness、anisometry、holes}
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?程序:
[c-sharp]?view plaincopy- read_image?(Image,?'G:/Halcon/機器視覺/images/bin_switch/bin_switch_3.png')??
- regiongrowing?(Image,?Regions,?3,?3,?1,?500)??
- area_center_gray?(Regions,?Image,?Area,?Row,?Column)??
- cooc_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_matrix?(Regions,?Image,?Matrix,?6,?0)??
- dev_set_paint?('histogram')??
- gray_projections?(Regions,?Image,?'simple',?HorProjection,?VertProjection)??
- histo_2dim?(Regions,?Image,?Image,?Histo2Dim)??
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運行結果:
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轉載于:https://www.cnblogs.com/qqhfeng/p/7247800.html
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