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Introduction to morphological operations
- Morphological Operators are set of kernels that can achieve a variety of effects such as reducing noise
- Certain operators are very good at reducing black points on a white background (and vice versa)
- Certain operators can also achieve an erosion and dilation effect that can add or erode from an existing image
- This effect is most easily seen on text data
- In a morphological operation, the value of each pixel in the output image is based on a comparison of the corresponding pixel in the input image with its neighbors
- uBy choosing the size and shape of the neighborhood, one can construct a morphological operation that is sensitive to the specific shapes in the input image
Morphological Operators
- Opening and Closing
- Dilation and erosion
- Gradient
They reshape objects in images and are vital for enhancing, extracting features, and reducing noise. These operations work on binary images, where each pixel is either black or white, using a small binary structure to define pixel neighborhoods. This structure can take various shapes, such as square, rectangle, circle, or diamond.
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