Morphology and its basic operations- A easy path towards computer vision
Morphology is structural processing of images. To recognize the image even more accurately, morphology can be performed. Morphology operations can vary from low level image processing to high level image processing which may include variety of factors. Broadly speaking, the operations of morphology can be divided into four major operations.
1. Erosion
2. Dilation
3. Open
4. Close
Erosion: — Erosion refers to the shrinking of an image by removing pixels from the boundaries. Thus, the output image is the minimum value of all the pixels of the boundaries in the image. In the lay man language, this can also be compared to the concept of soil erosion. Erosion means removal of the layer, and the soil erosion suggests the removal of topmost layer of soil from the surface and, hence leaving the other layers. Similarly, in computer vision, erosion suggests the removal of additional pixels in the boundary of the image to give the glimpse of actual image properly.
Dilation: — Dilation is the reverse of erosion. It is the maximum value of all the pixels in the neighborhood. This leads to the expansion of image so that the minute details are more clearly visible.
Combination of erosion and dilation: -
Open: — Open is erosion followed by dilation.
It means this operation first erodes the image and then dilate that eroded image. If the image has small objects that prevent the proper interpretation of the image, then closing operation is very useful as it make that objects noticeable.
Close: — Close is opposite of open. It means dilation followed by erosion. It is useful to fill the small holes present in the image that may help in the overall interpretation of the image.
