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形态学运算

膨胀、腐蚀、重新构造以及执行其他形态学运算

形态学是基于形状处理图像的一组广泛的图像处理运算。在形态学运算中,图像中的每个像素都基于其邻域中其他像素的值进行调整。通过选择邻域的大小和形状,您可以构造对输入图像中的特定形状敏感的形态学运算。

函数

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imerodeErode image
imdilateDilate image
imopenMorphologically open image
imcloseMorphologically close image
imtophatTop-hat filtering
imbothatBottom-hat filtering
imclearborderSuppress light structures connected to image border
imfillFill image regions and holes
bwhitmissBinary hit-miss operation
bwmorph针对二值图像的形态学运算
bwmorph3Morphological operations on binary volume
bwperimFind perimeter of objects in binary image
bwskelReduce all objects to lines in 2-D binary image or 3-D binary volume
bwulterodeUltimate erosion
imreconstructMorphological reconstruction
imregionalmaxRegional maxima
imregionalminRegional minima
imextendedmaxExtended-maxima transform
imextendedminExtended-minima transform
imhmaxH-maxima transform
imhminH-minima transform
imimposeminImpose minima
strelMorphological structuring element
offsetstrelMorphological offset structuring element
conndefCreate connectivity array
iptcheckconnCheck validity of connectivity argument
applylutNeighborhood operations on binary images using lookup tables
bwlookup Nonlinear filtering using lookup tables
makelutCreate lookup table for use with bwlookup
bwpackPack binary image
bwunpackUnpack binary image

主题

形态学的元素

形态学运算的类型

最基本的形态学运算是膨胀和腐蚀。您可以将膨胀和腐蚀结合起来进行更专门的运算。

Morphological Reconstruction

Morphological reconstruction is used to extract marked objects from an image without changing the object size or shape.

Structuring Elements

A structuring element defines the neighborhood used to process each pixel. A structuring element influences the size and shape of objects to process in the image.

Border Padding for Morphology

Morphological dilation and erosion pad the image border in different ways to avoid border effects.

Pixel Connectivity

Connectivity determines whether a center pixel and adjacent pixels belong to the same object.

Lookup Table Operations

A lookup table is a vector in which each element represents the different permutations of pixels in a neighborhood. Lookup tables are useful for custom erosion and dilation operations.

形态学的应用

Dilate an Image to Enlarge a Shape

Dilation adds pixels to boundary of an object. Dilation makes objects more visible and fills in small holes in the object.

Remove Thin Lines Using Erosion

Erosion removes pixels from the boundary of an object. Erosion removes islands and small objects so that only substantive objects remain.

Use Morphological Opening to Extract Large Image Features

You can use morphological opening to remove small objects from an image while preserving the shape and size of larger objects in the image.

Flood-Fill Operations

A flood fill operation assigns a uniform pixel value to connected pixels, stopping at object boundaries.

特色示例