In Halcon, create_component_model
is an operator for creating component-based shape models. The model is used to identify components of an object rather than treating the entire object as a whole. This operator accepts several parameters to define the components in the model and their properties. The following is an explanation of the parameters:
create_component_model (
ModelImage: image, // 输入参数,表示用于创建模型的图像
ComponentRegions: regions, // 输入参数,表示用于定义组件的区域(Regions)
MinScale: real, // 输入参数,表示组件的最小缩放尺度
MaxScale: real, // 输入参数,表示组件的最大缩放尺度
ScaleStep: real, // 输入参数,表示缩放步长
MinContrast: int, // 输入参数,表示最小对比度
NumLevels: int, // 输入参数,表示金字塔层数
AngleStart: real, // 输入参数,表示旋转角度起始值
AngleExtent: real, // 输入参数,表示旋转角度范围
AngleStep: real, // 输入参数,表示旋转角度步长
Metric: string, // 输入参数,表示匹配度量方法(例如:"use_polarity"或"ignore_global_polarity")
Contrast: real, // 输入参数,表示对比度增益
MinSize: int, // 输入参数,表示最小匹配区域的尺寸
NumMatches: tuple, // 输入参数,表示期望的匹配数量
SubPixel: string, // 输入参数,表示亚像素精度(例如:"true"或"false")
ModelType: string, // 输入参数,表示模型类型(例如:"none"、"use_polarity"等)
ModelID: int, // 输出参数,表示创建的模型的ID
RootRanking: root_ranking_type // 输出参数,表示根据模型创建的排名信息
)
By using create_component_model
operators, you can create a component-based shape model for identifying objects with similar components in images. After the model is created, you can use find_scaled_shape_models
the iso operator to find matching objects in the image.
Hope the above answer is helpful to you. If you have other questions, please feel free to ask.