一种新颖的基于截集分解的形态学算子

A novel kind of morphological operators induced by threshold decomposition

数学形态学算子在机器视觉应用领域中 ,如目标识别、图像分割及缺陷探测中越来越引起人们的重视。二值形态学基本操作膨胀与腐蚀也已经扩展到灰值图像处理中。目前已存在有几种不同的灰值形态学算子的定义 ,但对于结构元为灰值图的灰值图像处理 ,还未有一种具有实时处理结构的形态学算子。文中给出了这样的一种灰值形态学算子的定义。为了进一步增强这种算子的处理能力 ,在模糊集构成的完备格框架下完成了这种算子的构造过程。

Mathematical Morphology operators are becoming increasingly important in industrial vision application Binary morphological operations of dilation and erosion have been successfully extended to gray scale image processing Several different kinds of gray scale operators have been presented, but for the gray scale image processing with a gray scale structuring element, there have not been a kind of gray scale morphological operators with the structure applicable for real time image processing Such a kind of gray scale morphological operators' definitions is presented In order to further enhance the ability of this kind of operators for image processing The construction of this set of operators under the complete lattice of fuzzy sets was completed